Abstract
Wadi El Raiyan depression represents a discharge area of excess wastewater from the Faiyum province. It comprises two lakes: the upper lake connects the lower one through a channel. The intensive agriculture in the area hazardously affects both lakes. To assess the status of these lakes, this work studies the change detection using image classification and post-classification comparison, physicochemical parameters, concentration of trace elements, and microbiological contents. The classified images indicate a maintained constant area of the upper lake from 1990 to 2012 and decreased by 1.6% in 2014. The lower lake area increased by 4.8% between 1990 and 2001, then decreased till 2014 and increased again by 8.4% in 2015. The change detection concluded that the lake could be disappeared by 2019 if the exploitation of water from the upper lake continues, or the lake could be rebounded if the government planned to increase the recharge. The factor analysis implies that the total Fe, Mn, Ni, Ba, and As are controlled by pH–Eh relationship, Cu by TDS, Pb by temperature, while Cd is attributed to anthropogenic factor. The upper and lower lake samples exhibit biological oxygen demand (BOD) and chemical oxygen demand (COD) values lower than fish farm samples. The high BOD and COD values were coupled by high nitrate contents in the studied water samples. The cultivated land drains and the fish farms samples have total coliform (TC) and fecal coliform (FC) higher than the samples collected from the upper lake.
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References
Abd El-Kawy OA, Rød JK, Ismail HA, Suliman AS (2011) Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Appl Geogr 31:483–494
Abdel Wahed MSM, Mohamed EA, El-Sayed MI, M’nif A, Sillanpää M (2015) Hydrogeochemical processes controlling the water chemistry of a closed saline lake located in Sahara Desert: Lake Qarun, Egypt. Aquat Geochem 21(1):31–57
Biging GS, Chrisman NR, Colby DR, Congalton RG, Dobson JE, Ferguson RL, Goodchild MF, Jensen JR, Mace TH (1999) Accuracy assessment of remote sensing-detected change detection. In: Khorram S (ed) Monograph series of the American Society for Photogrammetry and Remote Sensing. American Society for Photogrammetry and Remote Sensing (ASPRS), Bethesd
Albertz J (2009) Einführung in die Fernerkundung. Darmstadt
Ali MH, Abdel-Satar AM (2005) Studies of some heavy metals in water, sediment, fish and fish diets in some fish farms in El-Fayoum Province. Egypt J Aquat Res 31(2):261–273
Almutairi A, Warner TA (2010) Change detection accuracy and image properties: a study using simulated data. Remote Sens 2(6):1508–1529
Area Fill (2017) Retrieved from https://hexagongeospatial.fluidtopics.net/#/reader/~P7L4c0T_d3papuwS98oGQ/NXrnFB_tDLpED9f_sa3kuA. Accessed 20 Jan 2017
Ayele GT, Demessie SS, Mengistu KT, Tilahun SA, Melesse AM (2016) Multitemporal land use/land cover change detection for the Batena Watershed, Rift Valley Lakes Basin, Ethiopia. In: Melesse AM, Abtew W (eds) Landscape Dynamics. Soils and Hydrological Processes in climates. Springer, Berlin, pp 51–72
Bottomley BR (1998) Mapping rural land use and land cover change in Carroll County, Arkansas utilizing multi-temporal Landsat Thematic Mapper satellite imagery. University of Arkansas, Diss. Arkansas
Brezonik P, William A (2011) Water Chemistry. An introduction to the chemistry of natural and engineered aquatic systems. Oxford University Press
Butt A, Shabbir R, Ahmad SS, Aziz N, Nawaz M, Shah MTA (2015) Land cover classification and change detection analysis of Rawal watershed using remote sensing data. J Biodivers Environ Sci 6:236–248
Campbell JB (1987) Introduction into remote sensing. The Guildford Press, New York
Campbell JB (2002) Introduction to remote sensing. Taylor and Francis. Conservation international foundation, London
Chen X, Vierling L, Deering D (2005) A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sens Environ 98:63–79
Clair NS, Perry LM, Gene FP (2003) Chemistry for environmental engineering and science. Mcgraw-Hill, New York
Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37–46
Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37(1):35–46
Congalton RG, Green K (1999) Assessing the accuracy of remotely sensed data: principles and practices. Lewis Publishers, New York
Congalton RG, Mead RA (1983) A quantitative method to test for consistency and correctness photointerepretation. Photogramm Eng Remote Sens 49:60–74
Coppin PR, Bauer ME (1996) Digital change detection in forest ecosystems with remote sensing imagery. Remote Sens Rev 13(3–4):207–234
Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Review article digital change detection methods in ecosystem monitoring: a review. Int J Remote Sens 25:1565–1596
EarthExplorer (2015) Retrieved from http://earthexplorer.usgs.gov/. Accessed 16 May 2015
Elewa AA, Shehata MB, Satar AA, Ali MHH, Gohar ME (2001) Effect of the drainage water on Lake Qarun ecosystem, Egypt. In 9th international Conference on the Conservation and Management of Lakes (Vol. 1116)
EOSQC (2015) Bottled/packaged drinking waters (other than natural mineral waters). Arab Republic of Egypt, Egyptian Organization of Standardization and Quality Control (EOSQC), E.S.: 1589/2005
ERDAS (2007) ERDAS imagine professional: tour guides. Norcross, GA: Leica Geosystems Geospatial Imaging, LLC
FAO (1972) Overall study of the Messara Plain. Report on Study of the Water Resources and their Exploitation for Irrigation in Eastern Crete, FAO Report No. AGL: SF/GRE/31
Filling the Gaps for Display (2016) Retrieved from https://landsat.usgs.gov/filling-gaps-display. Accessed 29 Nov 2016
Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80:185–201
Fung T, Le Drew E (1987) Application of principal components analysis to change detection. Photogramm Eng Remote Sens 53:1649–1658
Gao J (1999) A comparative study on spatial and spectral resolutions of satellite data in mapping mangrove forests. Int J Remote Sens 20:2823–2833
Gao J, Liu Y (2010) Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection. Int J Appl Earth Obs Geoinf 12:9–16
Giardino C, Bresciani M, Villa P, Martinelli A (2010) Application of remote sensing in water resource management: the case study of Lake Trasimeno, Italy. Water Resour Manag 24:3885–3899
Green EP, Clark CD, Mumby PJ, Edwards AJ, Ellis AC (1998) Remote sensing techniques for mangrove mapping. Int J Remote Sens 19:935–956
Geosystem L (2000) ERDAS field guide TM, 6th edn. Leica Geosystem, Atlanta
Glovis (2015) Retrieved from http://glovis.usgs.gov. Accessed 16 May 2015
Hammad MA, Abu El Einane S, Abed F (1983) Pedological studies on the Fayoum area, Egypt. I: landscapes and soil morphology. Egypt J Soil Sci 23(2):99–114
Hartter J, Lucas C, Gaughan AE, Aranda LL (2008) Detecting tropical dry forest succession in a shifting cultivation mosaic of the Yucatán Peninsula, Mexico. Appl Geogr 28:134–149
Hem JD (1985) Study and interpretation of the chemical characteristics of natural water. USGS water-supply paper 2254, 3rd ed. 263 p
Im N, Kawamura K, Suwandana E, Sakuno Y (2015) Monitoring land use and land cover effects on water quality in Cheung Ek Lake using ASTER images. Am J Environ Sci 11(1):1–12
Jabar A, Sadiq A, Sulong G, George LE (2014) Survey on gap filling algorithms in Landsat 7 ETM+ images. J Theor Appl Inf Technol 63:136–146
Janssen LL, Vanderwel FJ (1994) Accuracy assessment of satellite derived land-cover data: a review. Photogramm Eng Remote Sens 60:419–426
Jensen JR (1996) Introduction to digital image processing. Prentice Hall, Upper Saddle River, New Jersey 318
Kobayashi S, Lee GF (1978) Accumulation of arsenic in sediments of lakes treated with sodium arsenite. Environ Sci Technol 12(10):1195–1200
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174
Landsat 7 (2015) Retrieved from http://landsat.usgs.gov/about_landsat7.php. Accessed 20 Apr 2015
Landsat 8 (2015) Retrieved from http://landsat.gsfc.nasa.gov/?p=3186. Accessed 20 Apr 2015
Landsat Missions Timeline (2015) Retrived from https://landsat.usgs.gov/landsat-missions-timeline. Accessed 20 Apr 2015
Lee DS, Shan J, Bethel JS (2003) Class-guided building extraction from Ikonos imagery. Photogramm Eng Remote Sens 69:143–150
Li X, Yeh AGO (1998) Principal component analysis of stacked multi-temporal images for the monitoring of rapid urban expansion in the Pearl River Delta. Int J Remote Sens 19:1501–1518
Lillesand T, Kiefer R (2004) Remote sensing and image interpretation, Fifth edn. Wiley, New York
Lillesand TM, Kiefer RW (1994) Remote sensing and image interpretation. Wiley, USA
Lillesand TM, Kiefer RW (2000) Remote sensing and image interpretation. Wiley, New York
Livingstone DA (1963) Chemical composition of rivers and lakes. Data of Chemistry, U.S. Geological Survey Professional Paper 440 G, 1–64
Lu D, Mausel P, Brondizio E, Moran E (2004) Change detection techniques. Int J Remote Sens 25:2365–2401
Lunetta R S, Lyon JG (Eds.) (2004) Remote sensing and GIS accuracy assessment. CRC press
Macleod RD, Congalton RG (1998) A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed data. Photogramm Eng Remote Sens 64:207–216
Madugundu R, Al-Gaadi KA, Patil VC, Tola E (2014) Detection of land use and land cover changes in Dirab region of Saudi Arabia using remotely sensed imageries. Am J Environ Sci 10(1):8–18
Mansour SA, Sidky MM (2003) Ecotoxicological studies. 6. The first comparative study between Lake Qarun and Wadi El-Rayan wetland (Egypt), with respect to contamination of their major components. Food Chem 82(2):181–189
Mas JF (1999) Monitoring land-cover changes: a comparison of change detection techniques. Int J Remote Sens 20:139–152
Mei A, Manzo C, Fontinovo G, Bassani C, Allegrini A, Petracchini F (2016) Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data. J Afr Earth Sci 122:15–24
Mohamed EA, El-Kammar AM, Yehia MM, Abu Salem HS (2015) Hydrogeochemical evolution of inland lakes’ water: a study of major element geochemistry in the Wadi El Raiyan depression, Egypt. J Adv Res 6:1031–1044
Nalina P, Meenambal T, Sridhar RS (2014) Land use land cover dynamics of Nilgiris district, India inferred from satellite imageries. Am J Appl Sci 11:455
Nelson RF (1983) Detecting Forest canopy change due to insect activity using Landsat MSS. Photogramm Eng Remote Sens 49:1303–1314
Oskarsson A, Reeves AL (2007) Barium, in Nordberg, G., Fowler, B., Nordberg, M., Friberg, L., (Eds.), Handbook on the Toxicology of Metals, 3rd ed. Academic Press. pp. 407–414
Pierce ML, Moore CB (1980) Adsorption of arsenite on amorphous iron hydroxide from dilute aqueous solution. Environ Sci Eng Tech 14:214–216
Richards JA, Jia X (2006) Remote sensing digital image analysis. An Introduction, Berlin, Heidelberg
Said R (1993) The Nile River: geology, hydrology, and utilization. Elsevier, Amsterdam
Saleh MA, Ewane E, Jones J, Wilson BL (2000) Monitoring Wadi El Raiyan Lakes of the Egyptian desert for inorganic pollutants by ion-selective electrodes, ion chromatography, and inductively coupled plasma spectroscopy. Ecotox Environ Safe 45:310–316
Saleh MA, Saleh MA, Fouda MM, Saleh MA, Lattif MSA, Wilson BL (1988) Inorganic pollution of the man-made lakes of Wadi El-Raiyan and its impact on aquaculture and wildlife of the surrounding Egyptian desert. Arch Environ Contam Toxicol 17:391–403
Sayed MF, Abdel-Satar AM (2009) Chemical assessment of Wadi El-Rayan Lakes-Egypt. Am Eurasian J Agric Environ Sci 5:53–62
Scaramuzza P, Micijevic E, Chander G (2004) SLC gap-filled products phase one methodology. Landsat Technical Notes
Singh A (1989) Review article digital change detection techniques using remotely-sensed data. Int J Remote Sens 10:989–1003
Smits PC, Dellepiane SG, Schowengerdt RA (1999) Quality assessment of image classification algorithms for land-cover mapping: a review and a proposal for a cost-based approach. Int J Remote Sens 20:1461–1486
Son NT, Chen CF, Chang NB, Chen CR, Chang LY, Thanh BX (2015) Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam, using Landsat data and object-based image analysis. IEEE J Sel Top Appl Earth Obs Remote Sens 8:503–510
Stumm W, Morgan JJ (1970) Aquatic chemistry; an introduction emphasizing chemical equilibria in natural waters
Stumm W, Morgan JJ (1981) Aquatic chemistry. Wiley, New York
Tendaupenyu P, Magadza CHD, Murwira A (2016) Changes in landuse/landcover patterns and human population growth in the Lake Chivero catchment. Zimbabwe Geocarto Int:1–15
Thomas IL, Benning VM, Ching NP (1987) Classification of remotely sensed images. Adam Hilger, Bristol
Toll DL, Royal JA, Davis JB (1980 Urban area up-date procedures using Landsat Data. Proceedings of the Fall Technical Meeting of the American Society of Photogrammetry
WHO (2011) Guidelines for drinking-water quality. World Health Organization, 4th edition, Geneva, p. 541
Yang X, Lo CP (2002) Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. Int J Remote Sens 23:1775–1798
Yuan D, Elvidge CD, Lunetta RS (1998) Survey of multispectral methods for land cover change analysis. Remote sensing change detection: environmental monitoring methods and applications. Michigan’ Ann Arbor Press:21–39
Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change analysis of the twin cities (Minnesota) metropolitan area by multi-temporal Landsat remote sensing. Remote Sens Environ 98:317–328
Zhang C, Li W, Travis D (2007) Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach. Int J Remote Sens 28:5103–5122
Zinabu GM (1998) Human Interactions and Water Quality in the Horn of Africa. Science in Africa: Emerging Water Management Issues Symposium, Philadelphia
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The authors would like to express their appreciation to the team of the Central Chemical Analysis Laboratories of the National Water Research Centre, El-Kanater El-Khairia, Egypt, and the team of the Laboratory of Soil Science, Geography Institute, FAU (Friedrich-Alexander University), Erlangen, Germany for doing the analysis.
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This article is part of the Topical Collection on Current Advances in Geology of North Africa
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Abu Salem, H.S., Abu Khatita, A., Abdeen, M.M. et al. Geo-environmental evaluation of Wadi El Raiyan Lakes, Egypt, using remote sensing and trace element techniques. Arab J Geosci 10, 224 (2017). https://doi.org/10.1007/s12517-017-2991-3
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DOI: https://doi.org/10.1007/s12517-017-2991-3