Skip to main content

Advertisement

Log in

Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia

Analyse spatiale du potentiel d’eau souterraine à l’aide d’images satellites et d’évaluation multicritères à partir d’un SIG dans la vallée Raya, Ethiopie du Nord

Análisis espacial del potencial del agua subterránea usando sensores remotos y múltiples criterios de evaluación basados en GIS en el Raya Valley, norte de Etiopía

利用基于遥感及GIS的多标准评估方法对埃塞俄比亚北部Raya山谷进行地下水潜力空间分析

Análise espacial do potencial de água subterrânea através do uso de deteção remota e de avaliação multicritério com base em SIG no Vale de Raya, norte da Etiópia

  • Report
  • Published:
Hydrogeology Journal Aims and scope Submit manuscript

An Erratum to this article was published on 04 December 2014

Abstract

Sustainable development and management of groundwater resources require application of scientific principles and modern techniques. An integrated approach is implemented using remote sensing and geographic information system (GIS)-based multi-criteria evaluation to identify promising areas for groundwater exploration in Raya Valley, northern Ethiopia. The thematic layers considered are lithology, lineament density, geomorphology, slope, drainage density, rainfall and land use/cover. The corresponding normalized rates for the classes in a layer and weights for thematic layers are computed using Saaty’s analytical hierarchy process. Based on the computed rates and weights, aggregating the thematic maps is done using a weighted linear combination method to obtain a groundwater potential (GP) map. The GP map is verified by overlay analysis with observed borehole yield data. Map-removal and single-parameter sensitivity analyses are used to examine the effects of removing any of the thematic layers on the GP map and to compute effective weights, respectively. About 770 km2 (28 % of the study area) is designated as ‘very good’ GP. ‘Good’, ‘moderate’ and ‘poor’ GP areas cover 630 km2 (23 %), 600 km2 (22 %) and 690 km2 (25 %), respectively; the area with ‘very poor’ GP covers 55 km2 (2 %). Verification of the GP map against observed borehole yield data shows 74 % agreement, which is fairly satisfactory. The sensitivity analyses reveal the GP map is most sensitive to lithology with a mean variation index of 6.5 %, and lithology is the most effective thematic layer in GP mapping with mean effective weight of 52 %.

Résumé

Le développement durable et la gestion des eaux souterraines nécessitent l’application de principes scientifiques et de techniques modernes. Une approche intégrée est développée à partir d’images satellites et d’une évaluation multicritère basée sur un système d’informations géographiques (SIG) dans le but d’identifier des zones d’intérêt pour l’exploration des eaux souterraines dans la vallée Raya, au Nord de l’Ethiopie. Les couches thématiques considérées sont la lithologie, la densité de linéaments, la géomorphologie, la pente, la densité de drainage, la pluie et la couverture/utilisation du sol. Les taux normalisés des classes dans les couches correspondantes et les poids des couches thématiques sont calculés selon le procédé d’analyse hiérarchique de Saaty. A partir des taux et poids calculés, l’agrégation des cartes thématiques utilise une méthode de combinaison linéaire pondérée pour obtenir une carte de potentialité en eau souterraine (PES). La carte de PES est vérifiée par l’analyse de la superposition des débits de forages observés. Des retraits de carte et des analyses de sensibilités mono-paramètres sont utilisés respectivement pour examiner les effets de chaque couche thématique sur la carte de PES et pour calculer des poids effectifs. Environ 770 km2 (28 % de la zone d’étude) sont considérés comme de « très bonne » PES. Les PES « bonne », « modérée », et « faible » couvrent respectivement 630 km2 (23 %), 600 km2 (22 %) et 690 km2 (25 %); la surface des « très faibles » PES couvre 55 km2 (2 %). La vérification de la carte des PES avec les débits observés des forages montre une adéquation de 74 %, ce qui est assez satisfaisant. L’analyse de sensibilité révèle que la carte des PES est la plus sensible à la lithologie avec un index de variation de 6.5 %, et la lithologie est la carte thématique la plus déterminante sur la cartographie des PES avec un poids effectif moyen de 52 %.

Resumen

El manejo y desarrollo sustentable de los recursos de agua subterránea requieren la aplicación de principios científicos y técnicas modernas. Se implementa un enfoque integrado usando sensores remotos y múltiples criterios de evaluación basados en un sistema de información geográfico (GIS) para identificar áreas promisorias para la exploración de agua subterránea en el Raya Valley, norte de Etiopía. Las capas temáticas consideradas son litología, densidad de lineamientos, geomorfología, pendientes, densidad de drenaje, precipitación y uso / cubierta del suelo. Las tasas normalizadas correspondientes para las clases en una capa y los pesos para las capas temáticas se calcularon usando el proceso jerárquico analítico de Saaty. Basado en las tasas y pesos calculados, la agregación de los mapas temáticos se llevó a cabo usando el método de combinación linear ponderado para obtener un mapa del potencial de agua subterránea (GP). El mapa de GP se verifica por un análisis de superposición con datos provenientes de los rendimientos de las perforaciones. Se utilizó un análisis de eliminación de mapa y de sensibilidad de un solo parámetro para examinar los efectos de la remoción de cualquiera de las capas temáticas en el mapa de GP y para calcular los respectivos pesos efectivos. Alrededor de 770 km2 (28 % del área de estudio) se catalogó como un GP ‘muy bueno’. Las áreas con GP ‘bueno’, ‘moderado’ y ‘pobre’ cubren 630 km2 (23 %), 600 km2 (22 %) y 690 km2 (25 %), respectivamente; el área con GP ‘muy pobre’ cubre 55 km 2 (2 %).. La confrontación del mapa de GP con los datos de rendimientos observados de perforaciones muestran que un 74 % es bastante satisfactorio. Los análisis de sensibilidad revelaron que el mapa GP es más sensible a la litología con un índice de variación media de 6.5 %, y la litología es la capa temática más efectiva en el mapa GP con una peso efectivo media de 52 %.

摘要

地下水资源的可持续开发和管理需要应用科学的法则和现代技术。本研究采用了一个综合的研究方法,就是利用基于遥感和GIS的多标准评估方法确定埃塞俄比亚北部Raya山谷有希望的地下水勘察区。主要要考虑的项目有岩性、线性构造密度、地貌、坡度、排水系统密度、降雨及土地利用/土地覆盖层。利用Saaty层次分析法计算了主要项目的每项和权重中相应的标准化级别比率。根据计算的比率和权重,利用加权线性组合方法编制了主题图件,获取了地下水潜力图。地下水潜力图通过叠加分析和观测孔出水量资料验证。采用图件移除和单个参数敏感性分析法分别检查地下水潜力图中移除任何一个要素的效果及计算有效的权重。大约770 km2 (研究区的大约28 %)并标定为“有非常好的”地下水潜力。“好”、“中”和“差”的地下水潜力区为分别为630 km2 (23 %)、600 km2 (22 %)和 690 km2 (25 %)。“非常差的”地下水潜力区为55 km2 (2 %)。地下水潜力图与观测孔出水量资料有74%的一致性,这相当令人满意。灵敏度分析显示,地下水潜力图对平均变化指数达6.5 %的岩性最敏感,岩性是地下水潜力填图中最有效的要素,平均有效权重为52 %。

Resumo

O desenvolvimento sustentável e a gestão dos recursos de água subterrânea requerem a aplicação de princípios científicos e de técnicas modernas. É implementada uma abordagem integrada com uso de deteção remota e de um sistema multicritério de avaliação com base em informação geográfica (SIG) para identificar áreas promissoras para exploração de água subterrânea no Vale de Raya, no norte da Etiópia. As camadas temáticas consideradas são a litologia, a densidade dos lineamentos, a geomorfologia, o declive, a densidade de drenagem, a precipitação e a cobertura/uso do solo. As correspondentes taxas normalizadas para as classes numa camada e os pesos para as camadas temáticas são calculados utilizando o processo de hierarquia analítica de Saaty. Com base nas taxas e nos pesos calculados, a agregação dos mapas temáticos é feita através do uso de um método de combinação linear ponderada, para obter um mapa de potencial de água subterrânea (GP). O mapa GP é verificado através da análise de sobreposição com dados de produtividade observados em poços. São usadas análises de mapas de remoção e sensibilidade de parâmetro único para examinar os efeitos da remoção de qualquer das camadas temáticas no mapa GP e para calcular os pesos eficazes, respetivamente. Cerca de 770 km2 (28 % da área de estudo) é designada como GP ‘muito boa’. As áreas ‘boas’, ‘moderadas’ e ‘pobres’ cobrem respetivamente 630 km2 (23 %), 600 km2 (22 %) e 690 km2 (25 %); a área ‘muito pobre’ cobre 55 km2 (2 %). A verificação do mapa GP em relação aos dados de produtividade observados nos poços mostram 74 % de concordância, o que é satisfatório. A análise de sensibilidade revela que o mapa GP é mais sensível à litologia, com um índice de variação médio de 6.5 %, e a litologia é a camada temática mais efetiva no mapeamento GP, com um peso médio efetivo de 52 %.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Alemayehu T (2006) Groundwater occurrence in Ethiopia. Addis Ababa University, Addis Ababa, Ethiopia, 107 pp

    Google Scholar 

  • Awulachew SB, Yilma AD, Loulseged M, Loiskandl W, Ayana M, Alamirew T (2007) Water resources and irrigation development in Ethiopia. Working paper 123, IWMI, Colombo, Sri Lanka, 78 pp

    Google Scholar 

  • Ayenew T, GebreEgziabher M, Kebede S, Mamo S (2013) Integrated assessment of hydrogeology and water quality for groundwater-based irrigation development in the Raya Valley, northern Ethiopia. Water Int 38(4):480–492

    Article  Google Scholar 

  • Becker MW (2006) Potential for satellite remote sensing of groundwater. Groundwater 44(2):306–318

    Article  Google Scholar 

  • Berhanu B, Melesse AM, Seleshi Y (2013) GIS-based hydrological zones and soil geo-database of Ethiopia. Catena 104:21–31

    Article  Google Scholar 

  • Chowdhury A, Jha MK, Chowdary VM, Mal BC (2009) Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. Int J Remote Sens 30(1):231–250

    Article  Google Scholar 

  • Corgne S, Magagi R, Yergeau M, Sylla D (2010) An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS. Remote Sens Environ 114(9):1863–1875

    Article  Google Scholar 

  • Deshpande SM, Aher KR (2012) Evaluation of groundwater quality and its suitability for drinking and agriculture use in parts of Vaijapur, District Aurangabad, MS, India. Res J Chem Sci 2(1):25–31

    Google Scholar 

  • Ekneligoda TC, Henkel H (2010) Interactive spatial analysis of lineaments. Comput Geosci 36(8):1081–1090

    Article  Google Scholar 

  • Fashae OA, Tijani MN, Talabi AO, Adedeji OI (2014) Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach. Appl Water Sci 4(1):19–38

    Article  Google Scholar 

  • Fetter CW (1994) Applied hydrogeology, 3rd edn. Prentice Hall, Upper Saddle River, NJ, 691 pp

  • Hagosa F, Makombe G, Namara RE, Awulachew SB (2010) Importance of irrigated agriculture to the Ethiopian economy: capturing the direct net benefits of irrigation. IWMI Research Report, vol 128, IWMI, Colombo, Sri Lanka, pp 37

  • Hammouri N, El-Naqa A, Barakat M (2012) An integrated approach to groundwater exploration using remote sensing and geographic information system. J Water Resour Prot 4:717–724

    Article  Google Scholar 

  • Hanjra MA, Qureshi ME (2010) Global water crisis and future food security in an era of climate change. Food Policy 35(5):365–377

    Article  Google Scholar 

  • Hirano A, Welch R, Lang H (2003) Mapping from ASTER stereo image data: DEM validation and accuracy assessment. ISPRS J Photogramm Remote Sens 57(5):356–370

    Article  Google Scholar 

  • Hoffmann J (2005) The future of satellite remote sensing in hydrogeology. Hydrogeol J 13(1):247–250

    Article  Google Scholar 

  • Jaiswal RK, Mukherjee S, Krishnamurthy J, Saxena R (2003) Role of remote sensing and GIS techniques for generation of groundwater prospect zone towards rural development: an approach. Int J Remote Sens 24(5):993–1008

    Article  Google Scholar 

  • Jensen JR (2004) Introductory digital image processing: a remote sensing perspective, 3rd edn. Prentice Hall, Upper Saddle River, NJ, 544 pp

    Google Scholar 

  • Kumar PKD, Gopinath G, Seralathan P (2007) Application of remote sensing and GIS for demarcation of ground water potential zones of a river basin in Kerala, southwest coast of India. Int J Remote Sens 28(24):5583–5601

    Article  Google Scholar 

  • Lee GF, Jones-Lee A (1999) Evaluation of surface water quality impacts of hazardous chemical sites. Remediation 9(2):87–113

    Article  Google Scholar 

  • Lillesand MT, Kiefer WR, Chipman J (2008) Remote sensing and image interpretation, 6th edn. Wiley, New York, 768 pp

    Google Scholar 

  • Lodwick WA, Monson W, Svoboda L (1990) Attribute error and sensitivity analysis of map operations in geographical information systems: suitability analysis. Int J Geogr Inf Syst 4(4):413–428

    Article  Google Scholar 

  • Machiwal D, Jha MK, Singh PK, Mahnot SC, Gupta A (2004) Planning and design of cost-effective water harvesting structures for efficient utilization of scarce water resources in semi-arid regions of Rajasthan, India. Water Resour Manag 18(3):219–235

    Article  Google Scholar 

  • Machiwal D, Jha MK, Mal BC (2011) Assessment of groundwater potential in a semiarid region of India using remote sensing, GIS and MCDM techniques. Water Resour Manag 25(5):1359–1386

    Article  Google Scholar 

  • Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York, 408 pp

    Google Scholar 

  • Meijerink AMJ (1996) Remote sensing applications to hydrology: groundwater. Hydrol Sci J 41(4):549–561

    Article  Google Scholar 

  • Mengesha T, Tadios C, Workneh H (1996) Explanation of the geological map of Ethiopia. Ethiopian Geological Survey, Addis Ababa, Ethiopia

    Google Scholar 

  • Morris BL, Lawrence ARL, Chilton PJC, Adams B, Calow RC, Ba K (2003) Groundwater and its susceptibility to degradation: a global assessment of the problem and options for management. Early Warning and Assessment Report Series, RS. 03–3, United Nations Environment Program, Nairobi, Kenya, 126 pp

  • Nadew D (2003) Aquifer characterization and hydro-chemical investigation in the Raya Valley, northern Ethiopia. PHD Thesis, University of Life Sciences (Boku), Vienna, 204 pp

  • Napolitano P, Fabbri AG (1996) Single parameter sensitivity analysis for aquifer vulnerability assessment using DRASTIC and SINTACS. In: Kovar K, Nachtnebel HP (eds) ProcHydroGIS: application of geographical information systems in hydrology and water resources management, IAHS Publ. 235. IAHS, Wallingford, UK, pp 559–566

  • Prasanna MV, Chidambaram S, Hameed AS, Srinivasamoorthy K (2011) Hydrogeochemical analysis and evaluation of groundwater quality in the Gadilam River basin, Tamil Nadu, India. J Earth Syst Sci 120(1):85–98

    Article  Google Scholar 

  • Rai B, Tiwar A, Dubey VS (2005) Identification of groundwater prospective zones by using remote sensing and geoelectrical methods in Jharia and Raniganj coalfields, Dhanbad district, Jharkhand state. J Earth Syst Sci 114(5):515–522

    Article  Google Scholar 

  • Rango A, Shalaby AI (1998) Operational applications of remote sensing in hydrology: success, prospects and problems. Hydrol Sci J 43(6):947–968

    Article  Google Scholar 

  • Rao YS, Jugran DK (2003) Delineation of groundwater potential zones and zones of groundwater quality suitable for domestic purposes using remote sensing and GIS. Hydrol Sci J 48(5):821–833

    Article  Google Scholar 

  • Roscoe MO (1990) Handbook of groundwater development. Wiley, New York, 512 pp

    Book  Google Scholar 

  • Rose RS, Krishnan N (2009) Spatial analysis of groundwater potential using remote sensing and GIS in the Kanyakumari and Nambiyar basins, India. J Indian Soc Remote Sens 37(4):681–692

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York, 278 pp

    Google Scholar 

  • Saraf AK, Choudhury PR (1998) Integrated remote sensing and GIS for ground water exploration and identification of artificial recharges sites. Int J Remote Sens 19(10):1825–1841

    Article  Google Scholar 

  • Sayre R, Comer P, Hak J, Josse C, Bow J, Warner H, Larwanou M, Kelbessa E, Bekele T, Kehl H, Amena R, Andriamasimanana R, Ba T, Benson L, Boucher T, Brown M, Cress J, Dassering O, Friesen B, Gachathi F, Houcine S, Keita M, Khamala E, Marangu D, Mokua F, Morou B, Mucina L, Mugisha S, Mwavu E, Rutherford M, Sanou P, Syampungani S, Tomor B, Vall A, Vande Weghe J, Wangui E, Waruingi L (2013) A new map of standardized terrestrial ecosystems of Africa. Association of American Geographers, Washington, DC, 24 pp

    Google Scholar 

  • Sener E, Davraz A, Ozcelik M (2005) An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrogeol J 13(5–6):826–834

    Article  Google Scholar 

  • Simeonova V, Stratisb JA, Samarac C, Zachariadisb G, Voutsac D, Anthemidis A, Sofonioub M, Kouimtzisc T (2003) Assessment of the surface water quality in northern Greece. Water Res 37(17):4119–4124

    Article  Google Scholar 

  • Sturm M, Zimmermann M, Schütz K, Urban W, Hartung H (2009) Rainwater harvesting as an alternative water resource in rural sites in central northern Namibia. Phys Chem Earth Pt A/B/C 34(13):776–785

    Article  Google Scholar 

  • Tweed SO, Leblanc M, Webb JA, Lubczynski MW (2007) Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia. Hydrogeol J 15(1):75–96

    Article  Google Scholar 

  • Vreke J (1994) Optimal allocation of surface water in regional water management. Water Resour Manag 8(2):137–153

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge Mekelle University for the research fund through its NORAD-III project (I-GEOS/MU-UMB/03/2012). The authors also acknowledge the National Meteorology Agency (NMA) of Ethiopia, Tigray Region Water Bureau and Relief Society of Tigray (REST) for providing rainfall and borehole yield data. The two anonymous reviewers and editors are gratefully acknowledged for their valuable comments on our manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ayele Almaw Fenta.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fenta, A.A., Kifle, A., Gebreyohannes, T. et al. Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrogeol J 23, 195–206 (2015). https://doi.org/10.1007/s10040-014-1198-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10040-014-1198-x

Keywords

Navigation