Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach

Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-...
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Autor*in:	Sayl, Khamis Naba [verfasserIn] Muhammad, Nur Shazwani [verfasserIn] Yaseen, Zaher Mundher [verfasserIn] El-shafie, Ahmed [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Arid and semi-arid environments Remote sensing Geographic information system Elevation-area-volume curve Iraq

Übergeordnetes Werk:	Enthalten in: Water resources management - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987, 30(2016), 9 vom: 08. Mai, Seite 3299-3313
Übergeordnetes Werk:	volume:30 ; year:2016 ; number:9 ; day:08 ; month:05 ; pages:3299-3313

Links:	Volltext

DOI / URN:	10.1007/s11269-016-1350-6

Katalog-ID:	SPR018392148

Internformat


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520			\|a Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.
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700	1		\|a El-shafie, Ahmed \|e verfasserin \|4 aut
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matchkey_str	article:15731650:2016----::siainhpyiavralsfanaehretnsseuignertdi
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allfields	10.1007/s11269-016-1350-6 doi (DE-627)SPR018392148 (SPR)s11269-016-1350-6-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Sayl, Khamis Naba verfasserin aut Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy. Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213 Muhammad, Nur Shazwani verfasserin aut Yaseen, Zaher Mundher verfasserin aut El-shafie, Ahmed verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 30(2016), 9 vom: 08. Mai, Seite 3299-3313 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313 https://dx.doi.org/10.1007/s11269-016-1350-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 30 2016 9 08 05 3299-3313
spelling	10.1007/s11269-016-1350-6 doi (DE-627)SPR018392148 (SPR)s11269-016-1350-6-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Sayl, Khamis Naba verfasserin aut Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy. Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213 Muhammad, Nur Shazwani verfasserin aut Yaseen, Zaher Mundher verfasserin aut El-shafie, Ahmed verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 30(2016), 9 vom: 08. Mai, Seite 3299-3313 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313 https://dx.doi.org/10.1007/s11269-016-1350-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 30 2016 9 08 05 3299-3313
allfields_unstemmed	10.1007/s11269-016-1350-6 doi (DE-627)SPR018392148 (SPR)s11269-016-1350-6-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Sayl, Khamis Naba verfasserin aut Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy. Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213 Muhammad, Nur Shazwani verfasserin aut Yaseen, Zaher Mundher verfasserin aut El-shafie, Ahmed verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 30(2016), 9 vom: 08. Mai, Seite 3299-3313 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313 https://dx.doi.org/10.1007/s11269-016-1350-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 30 2016 9 08 05 3299-3313
allfieldsGer	10.1007/s11269-016-1350-6 doi (DE-627)SPR018392148 (SPR)s11269-016-1350-6-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Sayl, Khamis Naba verfasserin aut Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy. Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213 Muhammad, Nur Shazwani verfasserin aut Yaseen, Zaher Mundher verfasserin aut El-shafie, Ahmed verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 30(2016), 9 vom: 08. Mai, Seite 3299-3313 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313 https://dx.doi.org/10.1007/s11269-016-1350-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 30 2016 9 08 05 3299-3313
allfieldsSound	10.1007/s11269-016-1350-6 doi (DE-627)SPR018392148 (SPR)s11269-016-1350-6-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Sayl, Khamis Naba verfasserin aut Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy. Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213 Muhammad, Nur Shazwani verfasserin aut Yaseen, Zaher Mundher verfasserin aut El-shafie, Ahmed verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 30(2016), 9 vom: 08. Mai, Seite 3299-3313 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313 https://dx.doi.org/10.1007/s11269-016-1350-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 30 2016 9 08 05 3299-3313
language	English
source	Enthalten in Water resources management 30(2016), 9 vom: 08. Mai, Seite 3299-3313 volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313
sourceStr	Enthalten in Water resources management 30(2016), 9 vom: 08. Mai, Seite 3299-3313 volume:30 year:2016 number:9 day:08 month:05 pages:3299-3313
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Arid and semi-arid environments Remote sensing Geographic information system Elevation-area-volume curve Iraq
dewey-raw	550
isfreeaccess_bool	false
container_title	Water resources management
authorswithroles_txt_mv	Sayl, Khamis Naba @@aut@@ Muhammad, Nur Shazwani @@aut@@ Yaseen, Zaher Mundher @@aut@@ El-shafie, Ahmed @@aut@@
publishDateDaySort_date	2016-05-08T00:00:00Z
hierarchy_top_id	315299924
dewey-sort	3550
id	SPR018392148
language_de	englisch
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author	Sayl, Khamis Naba
spellingShingle	Sayl, Khamis Naba ddc 550 bkl 43.33 misc Arid and semi-arid environments misc Remote sensing misc Geographic information system misc Elevation-area-volume curve misc Iraq Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
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topic_title	550 630 ASE 43.33 bkl Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach Arid and semi-arid environments (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Geographic information system (dpeaa)DE-He213 Elevation-area-volume curve (dpeaa)DE-He213 Iraq (dpeaa)DE-He213
topic	ddc 550 bkl 43.33 misc Arid and semi-arid environments misc Remote sensing misc Geographic information system misc Elevation-area-volume curve misc Iraq
topic_unstemmed	ddc 550 bkl 43.33 misc Arid and semi-arid environments misc Remote sensing misc Geographic information system misc Elevation-area-volume curve misc Iraq
topic_browse	ddc 550 bkl 43.33 misc Arid and semi-arid environments misc Remote sensing misc Geographic information system misc Elevation-area-volume curve misc Iraq
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title	Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
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title_full	Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
author_sort	Sayl, Khamis Naba
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author_browse	Sayl, Khamis Naba Muhammad, Nur Shazwani Yaseen, Zaher Mundher El-shafie, Ahmed
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title_sort	estimation the physical variables of rainwater harvesting system using integrated gis-based remote sensing approach
title_auth	Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
abstract	Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.
abstractGer	Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.
abstract_unstemmed	Abstract Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.
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title_short	Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
url	https://dx.doi.org/10.1007/s11269-016-1350-6
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author2	Muhammad, Nur Shazwani Yaseen, Zaher Mundher El-shafie, Ahmed
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doi_str	10.1007/s11269-016-1350-6
up_date	2024-07-03T19:21:42.990Z
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Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach

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