Evaluation of groundwater potential using geospatial techniques View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-09

AUTHORS

Abdul-Aziz Hussein, Vanum Govindu, Amare Gebre Medhin Nigusse

ABSTRACT

The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas. More... »

PAGES

2447-2461

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13201-016-0433-0

DOI

http://dx.doi.org/10.1007/s13201-016-0433-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043029940


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/2008/0406", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Geography and Environmental Geoscience", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Mekelle University", 
          "id": "https://www.grid.ac/institutes/grid.30820.39", 
          "name": [
            "Institute of Geo-Information and Earth Observation Sciences, Mekelle University, Mekelle, Ethiopia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hussein", 
        "givenName": "Abdul-Aziz", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Mekelle University", 
          "id": "https://www.grid.ac/institutes/grid.30820.39", 
          "name": [
            "Department of Geo-Information and Earth Observation Sciences for Natural Resource Management, Institute of Geo-Information and Earth Observation Sciences, Mekelle University, Mekelle, Ethiopia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Govindu", 
        "givenName": "Vanum", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Mekelle University", 
          "id": "https://www.grid.ac/institutes/grid.30820.39", 
          "name": [
            "Department of Geo-Information and Earth Observation Sciences for Natural Resource Management, Institute of Geo-Information and Earth Observation Sciences, Mekelle University, Mekelle, Ethiopia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nigusse", 
        "givenName": "Amare Gebre Medhin", 
        "id": "sg:person.015161710065.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015161710065.56"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s10040-001-0167-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003333269", 
          "https://doi.org/10.1007/s10040-001-0167-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jhydrol.2007.10.032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006497090"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.margen.2016.01.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007949954"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12524-009-0058-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014926514", 
          "https://doi.org/10.1007/s12524-009-0058-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12524-009-0058-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014926514", 
          "https://doi.org/10.1007/s12524-009-0058-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1099-1085(199805)12:6<957::aid-hyp665>3.0.co;2-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015870849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1099-1085(199805)12:6<957::aid-hyp665>3.0.co;2-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015870849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/87559129709541104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035977089"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scitotenv.2014.05.048", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036940103"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-59583-7_14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039092286", 
          "https://doi.org/10.1007/978-3-642-59583-7_14"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-59583-7_14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039092286", 
          "https://doi.org/10.1007/978-3-642-59583-7_14"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-1694(92)90212-e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044854697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-1694(92)90212-e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044854697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/hess-17-4713-2013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049686856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10040-004-0379-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052251428", 
          "https://doi.org/10.1007/s10040-004-0379-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13201-013-0127-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052791151", 
          "https://doi.org/10.1007/s13201-013-0127-9"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-09", 
    "datePublishedReg": "2017-09-01", 
    "description": "The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13201-016-0433-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1051421", 
        "issn": [
          "2190-5487", 
          "2190-5495"
        ], 
        "name": "Applied Water Science", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "name": "Evaluation of groundwater potential using geospatial techniques", 
    "pagination": "2447-2461", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ccf75a7598b45605341b145091eefdbc4ccfca1596fc39a96a1c11361e72e333"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13201-016-0433-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1043029940"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13201-016-0433-0", 
      "https://app.dimensions.ai/details/publication/pub.1043029940"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:39", 
    "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/v90/0000000363_0000000363/records_70046_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs13201-016-0433-0"
  }
]
 

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/s13201-016-0433-0'

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/s13201-016-0433-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13201-016-0433-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13201-016-0433-0'


 

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

115 TRIPLES      21 PREDICATES      39 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13201-016-0433-0 schema:about anzsrc-for:04
2 anzsrc-for:0406
3 schema:author N8023c7271d9a4ba8ac6c3a146ed33ef7
4 schema:citation sg:pub.10.1007/978-3-642-59583-7_14
5 sg:pub.10.1007/s10040-001-0167-3
6 sg:pub.10.1007/s10040-004-0379-4
7 sg:pub.10.1007/s12524-009-0058-y
8 sg:pub.10.1007/s13201-013-0127-9
9 https://doi.org/10.1002/(sici)1099-1085(199805)12:6<957::aid-hyp665>3.0.co;2-j
10 https://doi.org/10.1016/0022-1694(92)90212-e
11 https://doi.org/10.1016/j.jhydrol.2007.10.032
12 https://doi.org/10.1016/j.margen.2016.01.003
13 https://doi.org/10.1016/j.scitotenv.2014.05.048
14 https://doi.org/10.1080/87559129709541104
15 https://doi.org/10.5194/hess-17-4713-2013
16 schema:datePublished 2017-09
17 schema:datePublishedReg 2017-09-01
18 schema:description The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.
19 schema:genre research_article
20 schema:inLanguage en
21 schema:isAccessibleForFree true
22 schema:isPartOf Nd99a68e4f3834b61b74707323f367966
23 Ne55d8d0725824c949857133feb9ed5ce
24 sg:journal.1051421
25 schema:name Evaluation of groundwater potential using geospatial techniques
26 schema:pagination 2447-2461
27 schema:productId N0787c92bcfdd45c69d99c1bb2c7bdc56
28 N1cddb0dadafb4fb3bda181330980eeaa
29 N2e4f2e75822e4962a769162f72c119f2
30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043029940
31 https://doi.org/10.1007/s13201-016-0433-0
32 schema:sdDatePublished 2019-04-11T12:39
33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
34 schema:sdPublisher N6d8775c98f4941ccb1c69b62aa884e87
35 schema:url https://link.springer.com/10.1007%2Fs13201-016-0433-0
36 sgo:license sg:explorer/license/
37 sgo:sdDataset articles
38 rdf:type schema:ScholarlyArticle
39 N0787c92bcfdd45c69d99c1bb2c7bdc56 schema:name doi
40 schema:value 10.1007/s13201-016-0433-0
41 rdf:type schema:PropertyValue
42 N1cddb0dadafb4fb3bda181330980eeaa schema:name readcube_id
43 schema:value ccf75a7598b45605341b145091eefdbc4ccfca1596fc39a96a1c11361e72e333
44 rdf:type schema:PropertyValue
45 N2e4f2e75822e4962a769162f72c119f2 schema:name dimensions_id
46 schema:value pub.1043029940
47 rdf:type schema:PropertyValue
48 N6d8775c98f4941ccb1c69b62aa884e87 schema:name Springer Nature - SN SciGraph project
49 rdf:type schema:Organization
50 N8023c7271d9a4ba8ac6c3a146ed33ef7 rdf:first Nd530a006dba84facb8002de03c13f76e
51 rdf:rest Naea51fade2c64f8fa134764c0fa8b488
52 Na784ebe95c9844f89664e0e78ebd5b8b rdf:first sg:person.015161710065.56
53 rdf:rest rdf:nil
54 Naea51fade2c64f8fa134764c0fa8b488 rdf:first Nfe16addb89804d939886ce8133e1e4af
55 rdf:rest Na784ebe95c9844f89664e0e78ebd5b8b
56 Nd530a006dba84facb8002de03c13f76e schema:affiliation https://www.grid.ac/institutes/grid.30820.39
57 schema:familyName Hussein
58 schema:givenName Abdul-Aziz
59 rdf:type schema:Person
60 Nd99a68e4f3834b61b74707323f367966 schema:volumeNumber 7
61 rdf:type schema:PublicationVolume
62 Ne55d8d0725824c949857133feb9ed5ce schema:issueNumber 5
63 rdf:type schema:PublicationIssue
64 Nfe16addb89804d939886ce8133e1e4af schema:affiliation https://www.grid.ac/institutes/grid.30820.39
65 schema:familyName Govindu
66 schema:givenName Vanum
67 rdf:type schema:Person
68 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
69 schema:name Earth Sciences
70 rdf:type schema:DefinedTerm
71 anzsrc-for:0406 schema:inDefinedTermSet anzsrc-for:
72 schema:name Physical Geography and Environmental Geoscience
73 rdf:type schema:DefinedTerm
74 sg:journal.1051421 schema:issn 2190-5487
75 2190-5495
76 schema:name Applied Water Science
77 rdf:type schema:Periodical
78 sg:person.015161710065.56 schema:affiliation https://www.grid.ac/institutes/grid.30820.39
79 schema:familyName Nigusse
80 schema:givenName Amare Gebre Medhin
81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015161710065.56
82 rdf:type schema:Person
83 sg:pub.10.1007/978-3-642-59583-7_14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039092286
84 https://doi.org/10.1007/978-3-642-59583-7_14
85 rdf:type schema:CreativeWork
86 sg:pub.10.1007/s10040-001-0167-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003333269
87 https://doi.org/10.1007/s10040-001-0167-3
88 rdf:type schema:CreativeWork
89 sg:pub.10.1007/s10040-004-0379-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052251428
90 https://doi.org/10.1007/s10040-004-0379-4
91 rdf:type schema:CreativeWork
92 sg:pub.10.1007/s12524-009-0058-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1014926514
93 https://doi.org/10.1007/s12524-009-0058-y
94 rdf:type schema:CreativeWork
95 sg:pub.10.1007/s13201-013-0127-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052791151
96 https://doi.org/10.1007/s13201-013-0127-9
97 rdf:type schema:CreativeWork
98 https://doi.org/10.1002/(sici)1099-1085(199805)12:6<957::aid-hyp665>3.0.co;2-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1015870849
99 rdf:type schema:CreativeWork
100 https://doi.org/10.1016/0022-1694(92)90212-e schema:sameAs https://app.dimensions.ai/details/publication/pub.1044854697
101 rdf:type schema:CreativeWork
102 https://doi.org/10.1016/j.jhydrol.2007.10.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006497090
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1016/j.margen.2016.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007949954
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1016/j.scitotenv.2014.05.048 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036940103
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1080/87559129709541104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035977089
109 rdf:type schema:CreativeWork
110 https://doi.org/10.5194/hess-17-4713-2013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049686856
111 rdf:type schema:CreativeWork
112 https://www.grid.ac/institutes/grid.30820.39 schema:alternateName Mekelle University
113 schema:name Department of Geo-Information and Earth Observation Sciences for Natural Resource Management, Institute of Geo-Information and Earth Observation Sciences, Mekelle University, Mekelle, Ethiopia
114 Institute of Geo-Information and Earth Observation Sciences, Mekelle University, Mekelle, Ethiopia
115 rdf:type schema:Organization
 




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


...