Evaluation of allowable withdrawn volume of groundwater based on observed data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-06

AUTHORS

Ye-Shuang Xu, Run-Qiu Huang, Jie Han, Shui-Long Shen

ABSTRACT

To control land subsidence due to groundwater withdrawal, it is important to estimate allowable withdrawn volume of groundwater in a soft deposit. This technical note presents a simple approach for estimating the allowable withdrawn volume of a deposit. A regression analysis method was used based on measured land subsidence and recorded net withdrawn volume. This approach was proposed based on the principle of soil compression at different effective stresses, i.e. the soil compression is small when the consolidation stress is lower than the yield stress of the deposit, but large when the consolidation stress is higher than the yield stress. Two case studies are presented in this technical paper to demonstrate how to use the simple approach to estimate the allowable withdrawn volume. More... »

PAGES

513-522

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11069-013-0576-3

DOI

http://dx.doi.org/10.1007/s11069-013-0576-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028760125


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0503", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Soil Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/05", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Chengdu University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.411288.6", 
          "name": [
            "Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China", 
            "State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xu", 
        "givenName": "Ye-Shuang", 
        "id": "sg:person.012360610177.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012360610177.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Chengdu University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.411288.6", 
          "name": [
            "State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "Run-Qiu", 
        "id": "sg:person.015313064241.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015313064241.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Kansas", 
          "id": "https://www.grid.ac/institutes/grid.266515.3", 
          "name": [
            "Civil, Environmental, and Architectural Engineering (CEAE) Department, The University of Kansas, 2150 Learned Hall, 1530\u00a0W. 15th Street, 66045-7609, Lawrence, KS, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Jie", 
        "id": "sg:person.013201504523.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013201504523.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Shanghai Jiao Tong University", 
          "id": "https://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China", 
            "State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China", 
            "State Key Laboratory of Ocean Engineering, 200240, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shen", 
        "givenName": "Shui-Long", 
        "id": "sg:person.010735570166.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010735570166.15"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1139/t11-049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004041961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-011-9859-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014386725", 
          "https://doi.org/10.1007/s11069-011-9859-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1745-6584.1984.tb01416.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015553545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1745-6584.1984.tb01416.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015553545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-007-9168-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016008763", 
          "https://doi.org/10.1007/s11069-007-9168-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3208/sandf.51.239", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017585967"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/0470848944.hsa164b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019694319"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-011-9851-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020803770", 
          "https://doi.org/10.1007/s11069-011-9851-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/nag.1125", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025031726"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.geotexmem.2009.01.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025100483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/t10-100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027841808"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.clay.2011.10.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033471145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-012-0220-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034807207", 
          "https://doi.org/10.1007/s11069-012-0220-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-010-9509-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035247074", 
          "https://doi.org/10.1007/s11069-010-9509-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-010-9509-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035247074", 
          "https://doi.org/10.1007/s11069-010-9509-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.enggeo.2009.08.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037149651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10040-012-0892-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052608123", 
          "https://doi.org/10.1007/s10040-012-0892-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10040-012-0892-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052608123", 
          "https://doi.org/10.1007/s10040-012-0892-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)cf.1943-5509.0000231", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057625331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)cf.1943-5509.0000278", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057625378"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)em.1943-7889.0000516", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057630064"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0000460", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057632431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0000553", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057632524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0000746", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057632716"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1680/geot.2004.54.2.143", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068211405"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1680/grim.2004.8.2.59", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068212583"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-06", 
    "datePublishedReg": "2013-06-01", 
    "description": "To control land subsidence due to groundwater withdrawal, it is important to estimate allowable withdrawn volume of groundwater in a soft deposit. This technical note presents a simple approach for estimating the allowable withdrawn volume of a deposit. A regression analysis method was used based on measured land subsidence and recorded net withdrawn volume. This approach was proposed based on the principle of soil compression at different effective stresses, i.e. the soil compression is small when the consolidation stress is lower than the yield stress of the deposit, but large when the consolidation stress is higher than the yield stress. Two case studies are presented in this technical paper to demonstrate how to use the simple approach to estimate the allowable withdrawn volume.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11069-013-0576-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7009625", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1050117", 
        "issn": [
          "0921-030X", 
          "1573-0840"
        ], 
        "name": "Natural Hazards", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "67"
      }
    ], 
    "name": "Evaluation of allowable withdrawn volume of groundwater based on observed data", 
    "pagination": "513-522", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "890158546345f7e4e38b3e22d450751b7d8c9debc1eaf07a45eacc4ad40d3611"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11069-013-0576-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1028760125"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11069-013-0576-3", 
      "https://app.dimensions.ai/details/publication/pub.1028760125"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T16:46", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8669_00000532.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs11069-013-0576-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11069-013-0576-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11069-013-0576-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11069-013-0576-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11069-013-0576-3'


 

This table displays all metadata directly associated to this object as RDF triples.

168 TRIPLES      21 PREDICATES      50 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11069-013-0576-3 schema:about anzsrc-for:05
2 anzsrc-for:0503
3 schema:author N5d0f322292794543af7f9a0459dac7b7
4 schema:citation sg:pub.10.1007/s10040-012-0892-9
5 sg:pub.10.1007/s11069-007-9168-4
6 sg:pub.10.1007/s11069-010-9509-6
7 sg:pub.10.1007/s11069-011-9851-3
8 sg:pub.10.1007/s11069-011-9859-8
9 sg:pub.10.1007/s11069-012-0220-7
10 https://doi.org/10.1002/0470848944.hsa164b
11 https://doi.org/10.1002/nag.1125
12 https://doi.org/10.1016/j.clay.2011.10.003
13 https://doi.org/10.1016/j.enggeo.2009.08.009
14 https://doi.org/10.1016/j.geotexmem.2009.01.001
15 https://doi.org/10.1061/(asce)cf.1943-5509.0000231
16 https://doi.org/10.1061/(asce)cf.1943-5509.0000278
17 https://doi.org/10.1061/(asce)em.1943-7889.0000516
18 https://doi.org/10.1061/(asce)gt.1943-5606.0000460
19 https://doi.org/10.1061/(asce)gt.1943-5606.0000553
20 https://doi.org/10.1061/(asce)gt.1943-5606.0000746
21 https://doi.org/10.1111/j.1745-6584.1984.tb01416.x
22 https://doi.org/10.1139/t10-100
23 https://doi.org/10.1139/t11-049
24 https://doi.org/10.1680/geot.2004.54.2.143
25 https://doi.org/10.1680/grim.2004.8.2.59
26 https://doi.org/10.3208/sandf.51.239
27 schema:datePublished 2013-06
28 schema:datePublishedReg 2013-06-01
29 schema:description To control land subsidence due to groundwater withdrawal, it is important to estimate allowable withdrawn volume of groundwater in a soft deposit. This technical note presents a simple approach for estimating the allowable withdrawn volume of a deposit. A regression analysis method was used based on measured land subsidence and recorded net withdrawn volume. This approach was proposed based on the principle of soil compression at different effective stresses, i.e. the soil compression is small when the consolidation stress is lower than the yield stress of the deposit, but large when the consolidation stress is higher than the yield stress. Two case studies are presented in this technical paper to demonstrate how to use the simple approach to estimate the allowable withdrawn volume.
30 schema:genre research_article
31 schema:inLanguage en
32 schema:isAccessibleForFree false
33 schema:isPartOf N05f1cdc4100f41308e61bc3ead8c7910
34 Na28862aa8cbc46d59838b2c34cc67980
35 sg:journal.1050117
36 schema:name Evaluation of allowable withdrawn volume of groundwater based on observed data
37 schema:pagination 513-522
38 schema:productId N0e15b8f410af4216bcb7a229f2c61204
39 Nd32e32f3829c4e939dae439ee5d8b1c2
40 Nf8549e08d60b4f1eb3ac22bcfec6e61c
41 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028760125
42 https://doi.org/10.1007/s11069-013-0576-3
43 schema:sdDatePublished 2019-04-10T16:46
44 schema:sdLicense https://scigraph.springernature.com/explorer/license/
45 schema:sdPublisher N8c7bac75b4664de29fe78bdbea1aa1e1
46 schema:url http://link.springer.com/10.1007%2Fs11069-013-0576-3
47 sgo:license sg:explorer/license/
48 sgo:sdDataset articles
49 rdf:type schema:ScholarlyArticle
50 N05f1cdc4100f41308e61bc3ead8c7910 schema:issueNumber 2
51 rdf:type schema:PublicationIssue
52 N0e15b8f410af4216bcb7a229f2c61204 schema:name dimensions_id
53 schema:value pub.1028760125
54 rdf:type schema:PropertyValue
55 N2c0c3f88d4524b07afc80dd3da865f1b rdf:first sg:person.013201504523.72
56 rdf:rest N79ea08b53bfe46aeaca7d71db1f90bc9
57 N409325aa268f429b8541bd967ca85cfc rdf:first sg:person.015313064241.33
58 rdf:rest N2c0c3f88d4524b07afc80dd3da865f1b
59 N5d0f322292794543af7f9a0459dac7b7 rdf:first sg:person.012360610177.07
60 rdf:rest N409325aa268f429b8541bd967ca85cfc
61 N79ea08b53bfe46aeaca7d71db1f90bc9 rdf:first sg:person.010735570166.15
62 rdf:rest rdf:nil
63 N8c7bac75b4664de29fe78bdbea1aa1e1 schema:name Springer Nature - SN SciGraph project
64 rdf:type schema:Organization
65 Na28862aa8cbc46d59838b2c34cc67980 schema:volumeNumber 67
66 rdf:type schema:PublicationVolume
67 Nd32e32f3829c4e939dae439ee5d8b1c2 schema:name readcube_id
68 schema:value 890158546345f7e4e38b3e22d450751b7d8c9debc1eaf07a45eacc4ad40d3611
69 rdf:type schema:PropertyValue
70 Nf8549e08d60b4f1eb3ac22bcfec6e61c schema:name doi
71 schema:value 10.1007/s11069-013-0576-3
72 rdf:type schema:PropertyValue
73 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
74 schema:name Environmental Sciences
75 rdf:type schema:DefinedTerm
76 anzsrc-for:0503 schema:inDefinedTermSet anzsrc-for:
77 schema:name Soil Sciences
78 rdf:type schema:DefinedTerm
79 sg:grant.7009625 http://pending.schema.org/fundedItem sg:pub.10.1007/s11069-013-0576-3
80 rdf:type schema:MonetaryGrant
81 sg:journal.1050117 schema:issn 0921-030X
82 1573-0840
83 schema:name Natural Hazards
84 rdf:type schema:Periodical
85 sg:person.010735570166.15 schema:affiliation https://www.grid.ac/institutes/grid.16821.3c
86 schema:familyName Shen
87 schema:givenName Shui-Long
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010735570166.15
89 rdf:type schema:Person
90 sg:person.012360610177.07 schema:affiliation https://www.grid.ac/institutes/grid.411288.6
91 schema:familyName Xu
92 schema:givenName Ye-Shuang
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012360610177.07
94 rdf:type schema:Person
95 sg:person.013201504523.72 schema:affiliation https://www.grid.ac/institutes/grid.266515.3
96 schema:familyName Han
97 schema:givenName Jie
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013201504523.72
99 rdf:type schema:Person
100 sg:person.015313064241.33 schema:affiliation https://www.grid.ac/institutes/grid.411288.6
101 schema:familyName Huang
102 schema:givenName Run-Qiu
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015313064241.33
104 rdf:type schema:Person
105 sg:pub.10.1007/s10040-012-0892-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052608123
106 https://doi.org/10.1007/s10040-012-0892-9
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/s11069-007-9168-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016008763
109 https://doi.org/10.1007/s11069-007-9168-4
110 rdf:type schema:CreativeWork
111 sg:pub.10.1007/s11069-010-9509-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035247074
112 https://doi.org/10.1007/s11069-010-9509-6
113 rdf:type schema:CreativeWork
114 sg:pub.10.1007/s11069-011-9851-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020803770
115 https://doi.org/10.1007/s11069-011-9851-3
116 rdf:type schema:CreativeWork
117 sg:pub.10.1007/s11069-011-9859-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014386725
118 https://doi.org/10.1007/s11069-011-9859-8
119 rdf:type schema:CreativeWork
120 sg:pub.10.1007/s11069-012-0220-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034807207
121 https://doi.org/10.1007/s11069-012-0220-7
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1002/0470848944.hsa164b schema:sameAs https://app.dimensions.ai/details/publication/pub.1019694319
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1002/nag.1125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025031726
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.clay.2011.10.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033471145
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.enggeo.2009.08.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037149651
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.geotexmem.2009.01.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025100483
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1061/(asce)cf.1943-5509.0000231 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057625331
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1061/(asce)cf.1943-5509.0000278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057625378
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1061/(asce)em.1943-7889.0000516 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057630064
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1061/(asce)gt.1943-5606.0000460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057632431
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1061/(asce)gt.1943-5606.0000553 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057632524
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1061/(asce)gt.1943-5606.0000746 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057632716
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1111/j.1745-6584.1984.tb01416.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1015553545
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1139/t10-100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027841808
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1139/t11-049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004041961
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1680/geot.2004.54.2.143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068211405
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1680/grim.2004.8.2.59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068212583
154 rdf:type schema:CreativeWork
155 https://doi.org/10.3208/sandf.51.239 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017585967
156 rdf:type schema:CreativeWork
157 https://www.grid.ac/institutes/grid.16821.3c schema:alternateName Shanghai Jiao Tong University
158 schema:name Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China
159 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
160 State Key Laboratory of Ocean Engineering, 200240, Shanghai, China
161 rdf:type schema:Organization
162 https://www.grid.ac/institutes/grid.266515.3 schema:alternateName University of Kansas
163 schema:name Civil, Environmental, and Architectural Engineering (CEAE) Department, The University of Kansas, 2150 Learned Hall, 1530 W. 15th Street, 66045-7609, Lawrence, KS, USA
164 rdf:type schema:Organization
165 https://www.grid.ac/institutes/grid.411288.6 schema:alternateName Chengdu University of Technology
166 schema:name Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China
167 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
168 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...