ASSESSMENT OF TEMPORAL AND SPATIAL ALTERATION IN COASTAL LAKES - EGYPT

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1 ASSESSMENT OF TEMPORAL AND SPATIAL ALTERATION IN COASTAL LAKES - EGYPT ABSTRACT Hala Abayazid Coastal Research Institute, National Water Research Center, Egypt, halazid@yahoo.com Northern region of Egypt host coastal lakes with distinguished characteristics. Special environmental importance was earned when northern lakes have been acknowledged nature reserve with rich aquatic biota and key role as host to migratory birds. Also, with growing concerns of climate change impact, northern lakes are considered the front line defense to Egypt against possible Mediterranean Sea level rise. However, deteriorating condition has been noticed and triggered a number of studies for reaching sustainability. This research employs satellite imageries and remote sensing techniques for monitoring temporal and spatial changes in coastal lakes, while analyze causeeffect of development activities in catchment, on one hand, and climate change on the other. The study shows how the remote sensing facilitate coverage of wider stretch (Manzala, Burullus, Edko and Bardawil coastal lakes) and longer period of time ( ), with reasonable resolution (30*30 meter). The study also demonstrates the notable difference in environmental structure alteration with time between coastal lakes within the Nile delta and coastal lake with catchment area in underdeveloped region. Analyzed results show that development activities in lake catchment have the principal impact on deteriorating aquatic system in coastal lakes, while climate change showed minor effect, backed by the observed modest changes in temperature and rainfall rates during the same three decades. Keywords: Coastal Lake, Remote Sensing, NDVI 1 INTRODUCTION Coastal Lakes are characterized with distinctive environment and water quality status that make them host of rich aquatic populations as well as migrant birds. However, lakes are susceptible to deteriorating conditions that threat sustainability of such promising ecological role (EEAA 2003, Elshinnawy, 2005). With growing concerns of climate change and possible impact on environmental systems, human intrusion and progressive development processes have had undeniable adverse fingerprints on maintaining healthy environment in coastal lakes of Egypt (Abayazid and Al-Shinnawy 2012). In this research imageries from Landsat covering three decades, the period from summer 1984 till summer 2014, were used to assess change pattern in coastal lakes and catchments. Criteria were based on detecting change in classified surface cover as well as defining altered vegetation density and healthiness, as governing factor of changes in coastal lake environment and hydrologic system. in lakes encourages active aquatic ecology and help improving drained water quality before reaching the Med. Sea. However, receiving nutrient levels that exceed the lake s capacity cause undesirable excessive vegetation. Consequently, uncontrollable vegetation density changes hydrodynamic and sediment movement/settlement within the lake. That in turn affects water quality; hence fish populations, in particular and aquatic flora and fauna in general. is also a governing factor in climate-related hydrologic cycle and water balance within lake, (Thomann & Mueller, 1987). Plant water intake and Evapo-Transpiration can affect and be affected by temperature and rainfall, presumably changing with climate change phenomenon. Therefore, difference in 598

2 classified surface cover and indexed vegetation was considered a good starting point for general assessment of evolving environmental status in coastal lake. Scholars have been using Normalized Difference Index (NDVI), ranging from -1 to +1 in value, as indication of density and healthiness of vegetation especially in relation to agricultural practices, reclamation development and catchment management. Reviewed researches showed successful application of remote sensing techniques in following changes in land cover and vegetation state in regions with certain interest. Recent research by Varshney (2013) discussed the use of Remote-sensing-based multi-temporal satellite imageries and land cover indices in determining changes in built-up regions with time through an application in India. In 2014, El-Shirbeny et al. presented a study that addresses using remote sensing technique in water resources management with agricultural requirements in Egypt. Authors used Landsat8 imageries covering the Nile delta and wadi (valley) for the month of August, Linearly relating NDVI to crop coefficient led to evaluation of potential crop Evapotranspiration, hence water requirement. Donia (2012) also used the NDVI for agricultural assessment in lake Qaroun watershed, located central of Egypt. The study addresses applying remote sensing imageries for having a comprehensive database for the lake served watershed. Earlier, in 1996, Lenney et al. presented a study in using NDVI to follow development in agricultural practices during the period from 1984 to 1993 in the Nile Delta and western desert of Egypt. The study proved effective use of NDVI in assessment of land lost to urbanization, on one hand, and progress in land reclamation, on the other. The importance of Northern coastal region of Egypt triggered many studies in order to address challenges as well as potentials. El-Gammal et al (2014) also used satellite imageries in detecting land cover and vegetation change in Damietta governorate of Egypt, in three time steps 1987, 2004 and The study demonstrates classified change in land vegetative status with time in terms of concluded NDVI thresholds. In 2012, Farag and El-Gamal presented a study about detecting phytoplankton biomass changes in Lake Burullus during The Chlorophyll-a levels were retrieved form satellite imageries visible and infrared bands, to be linked with nitrogen/phosphorusbased water quality parameters within the lake. Ahmed & Kaiser (2014) also presented a study that establish strong correlation between Chlorophyll and water temperature in lake Maryout, located west of the study area of current study, using thermal bands of Landsat images for the period 1986 till In this study, satellite-based NDVI and supervised cover classification are used to monitor alteration in structure and aquatic plants populating coastal lakes during three decades, from 1984 till 2014, in relation to climate change as well as developments in catchment area. Analyzed results proves effective use of remote sensing techniques in monitor changes in expanded region for long time, and establishing database yet with less cost and technical hassle. As lakes were selected with the purpose of precisely defining the reflective behavior to development process in served catchment, impact on environmental structure within Nile Delta lakes was found tightly linked to activities in catchment more than climate change. 2 MATERIALS AND METHODS 599

3 The research addresses changes in four main coastal lakes; Edko, Burullus, Manzalah and Bardawil, located North of Egypt, Fig. 1, in a strip bordered by coordinates 31 N E and N 30 E. Figure 1. Coastal lakes north of Egypt Satellite imageries of landsat with 30 m ground resolution; namely, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper Plus (ETM+), and Landsat-8 Operational Land Imager (OLI) were used to cover the period of study from July 1984 till June Time steps used in studying the changing surface cover and NDVI values in lakes are: 1984, 1987, 1990, 1998, 2001, 2003, 2006, 2011, and To get definite manifestation of changing vegetation cover within lakes and catchment, with no intrusion of growing/decaying phases of plants, imageries were selected for the same season in each year. Processing the satellite products; supervised classification, change detection and derived NDVI spatial distribution, were performed using ERDAS IMAGINE and Geographical Information Systems (ArcGIS) software. Using the multi-spectral remotely sensed imageries, NDVI was computed as the ratio of the measured intensities in the red (R) and near infrared (NIR) spectral bands. Commonly calculated by applying the following equation: NDVI = (NIR R)/ (NIR + R) (1) Computed NDVIs were classified so that poorly vegetated areas typically assumed with values ( ) while dense vegetation would have high NDVI values (0.6 to 0.8). Meanwhile, NDVI values less than 0.2 indicated as non-vegetated surface features such as water, barren land...etc. ( El-Shirbeny et al, 2014 and El-Gammal et al, 2014). Temperature and precipitation data covering the study period ( ) were obtained from the National Climatic Data Center (NOAA). Also consulted are predicted time series data from recommended global climate models of IPCC; Community Climate System Model, version3.0 (CCSM3.0)/ (ECHAM5)- MPI-OM model, of Max-Planck Institute for Meteorology Climate Model, accessed at web site addressed 3 RESULT ANALYSIS & DISCUSSION Average monthly temperature and precipitation rates for the period from 1984 till 2014 Fig. 2 confirm fairly steady trend with minor occasional raise. With average temperature of 20 C and mean total precipitation of 200mm, both seasonal temperature and rainfall occurrence have no persistence elevating trend that can be considered alarming. 600

4 30 Mean Monthly Temp Total Monthly Precipitation Figure 2. Mean monthly temperature and precipitation rates in three decades Coastal lakes within the Nile Delta region are receiving, beside the agricultural drainage waters, industrial and domestic wastewater discharges, as well as fish farming releases. Elevated nutrient content is reflected with increase in NDVI levels and vegetation intensity within lakes from 1984 to 2014; moderately in Lake Edko and highly in Lakes Manzalah and Burullus. Figure 3 gives an illustration of the change pattern in delta lakes. However, NDVI levels in catchment areas show certain decline in vegetation density and increase in urbanization, which second the conclusions of El- Gammal et al (2014). 601

5 1984 Lake Edko Lake Burullus Lakes Manzalah Lake Burullus 2014 Lake Edko Lakes Manzalah Land Cover; Bare/Urbanized Water Figure 3. Change in vegetative cover in Nile Delta lakes & catchments Oppositely, Bardawil Lake shows stable environmental status, with almost no change, except for scattered developments in catchment area. NDVI levels in lake and served catchment revealed no substantial change in thirty years, with mean NDVI value of ( -0.13) and standard deviation (STDEV) of (0.16) in 1984, while NDVI mean value reached only ( +0.01) with STDEV (0.09) in 2014, Fig. 4. These understandable low NDVI results reflect the effect of under-developed area in eastern coastal zone, served by Lake Bardawil. However, change detection showed certain scattered developments, Fig Figure 4. Spatial distribution of NDVI in Lake Bardawil &catchment with histogram ( ) 602

6 Figure 5. Scattered developments in Lake Bardawil catchment area in 2014 Results highlight the alarming environmental condition of coastal lakes located in the Nile Delta region, with special concerns to Manzalah and Burullus lakes. Both are suffering progressive shrink of waterbody with advancing development projects into lake waters, as well as increased vegetation intensity, particularly in south and western sides. An illustration of spatial difference in NDVI levels from 1984 to 2014 in Manzalah Lake and catchment area is given in Figure 6. Change detection revealed higher NDVI levels in catchment in initial year Meanwhile, by year 2014 parts of the lake water disappear, mostly in southern and western regions, replaced with soil, fish farms and vegetation. Gradual change of NDVI in sub-mapped Manzalah Lake is shown for selective time steps in Figures 7a&7b, indicating expanded vegetation area in lake. Supervised classification of Lake Manzalah surface cover was carried out to detect change during three decades. Figure 8 presents milestone of the gradual alteration in Lake Manzalah. Considerable acceleration in change rate was detected in the late 1990s and the first years of this millennium, with increase in developments within the lake to cover 65% of the area by Figure 6. NDVI in Lake Manzalah and catchment area ( ) 603

7 Figure 7a. Progressive change of NDVI in Lake Manzalah % of Lake Area Figure 7b. Expanded area of vegetation in Lake Manzalah Developments; Earthed/Fish farm Water Figure 8. Milestone of gradual alteration within Lake Manzalah 604

8 Evolution in Lake Burullus demonstrates similar trend of advancing earthed area as well as fish farms into Lake waters. Throughout thirty years, increased developments have been occurring, mostly in southern region of the lake, causing loss in water surface area with obvious impact on water quality status. Assessment of changes; using comparative analysis with surface cover supervised classification, Fig. 9, and spatially distributed NDVI levels, Fig. 10 and Fig. 11, indicate 39% increase in vegetative cover. Applying the quantifying criteria for vegetation state, using NDVIs graded values, revealed temporal trend of poor/moderate vegetation within Lake Burullus, Fig Developments; Earthed/Fish farm Water Figure 9. Temporal changes in Lake Burullus with supervised classification of surface cover Figure 10. Change with time in spatial NDVIs within Lake Burullus 605

9 Figure 11. Variability in Burullus vegetative content - NDVI histograms in 1984 and 2014 % Area of vegetative surface cover Poor Moderate Dense Figure 12. Classified change as % of Lake Burullus surface area in indicative time steps Detecting changes; by means of supervised cover classification and NDVIs analysis through time steps 1984, 1987, 1990, 1998, 2001, 2003, 2006, 2011, and 2014 proved active intrusion of developments into Edko Lake waters, in Eastern and Western sides; in terms of earthed section and fish farms. An illustration for selective time steps is given in Figure 13. About 43% of vegetative cover was replaced with developments and fish farms during these three decades, with faster pace since Shrunk area of lake surface water is found reaching about 15%; however change in water reflection intensity indicates the deteriorating status of Lake water quality

10 Developments; Earthed/Fish farm Water Figure 13. Spatial NDVIs and classified change in Lake Edko cover 4 CONCLUSION The study presented aspects of changing structure and aquatic environment in coastal lakes in Egypt, with reference to development process and climate change impact. Satellite imageries were retrieved in time steps from 1984 till 2014 inclusive, during summer seasons for consistency in vegetation stage. Hence, processed remotely sensed imageries provided changes in classified cover as well as spatial pattern of NDVIs and vegetative status in lakes and catchments. Results proved the prime effect of excessive wastewater discharges onto lakes with active catchment areas. On the other hand, changes in hydrology-related climate parameters were found fairly minor in a way that does not match the found drastic changes within the lakes in the delta coastal region, Edko, Burullus and Manzalah. Severe alterations were found in Lake Burullus and Lake Manzalah; with developments intruding further into the lake; via earthed areas and increasing fish farming activities, causing loss in water surface area as well as expand in aquatic vegetation, hence alarming deterioration in water quality. Opposed to that, Bardawil Lake showed mostly steady state during the last thirty years with minor developments in its catchment. Advances in satellite-based products and remote sensing techniques proved as effective monitoring tool that offer a vast pool of data with more frequent and expanded spatial coverage, conditioned with reasonable resolution. This research study presented the use of Earth Observation techniques in assessing aspects in environmental condition within lakes, and following changes throughout three decades, as well. The study managed establishing long term, spatially distributed, database for altered cover and vegetation content in four main coastal lakes, with possibility of future regular monitoring planning. Finally, further studies are recommended to reach restoration scheme for lakes Manzalah and Burulus in order to maintain their important environmental role. REFERENCES Abayazid, H. & Al-Shinnawy, I. (2012) Coastal Lake Sustainability: Threats and Opportunities with Climate Change. Journal of Mechanical and Civil Engineering of the International Organization of Scientific Research (JMCE/IOSR), 1(5), pp

11 Ahmed, S. &Kaiser, M. (2014) Monitoring Water Pollution of Lake Maryout on the Mediterranean Coast of Egypt. International Journal of Remote Sensing Applications, 4(1), pp , doi: /ijrsa Al-Burullus Wetland s Hydrological Study (2003) The Egyptian Environment Affairs Agency (EEAA), The Natural Protectorates Central Administration press, pp Donia, N. (2012) Application of remotely sensed imagery to watershed analysis: a case study of lake Qaroun, Egypt. International Water Technology Journal IWTJ, 2(1), pp El-Gammal, M., Ali, R. & Abou Samra, R.(2014) NDVI Threshold Classification for Detecting Cover in Damietta Governorate, Egypt. Journal of American Science, 10(8), pp Elshinnawy, I. (2005).Al-Burullus Hydrological Study, Natural Protectorates Department, Egyptian Environmental Affairs Agency (EEAA), Ministry of State for Environmental Affairs, Cairo, Egypt El-Shirbeny, M., Ali, A., Saleh, N. (2014) Crop Water Requirements in Egypt Using Remote Sensing Techniques. Journal of Agricultural Chemistry and Environment, 3, pp , Farag, H. & El-Gamal, A. (2012) Assessment of the Eutrophic Status of Lake Burullus (Egypt) using Remote Sensing. International Journal of Environmental Science and Engineering (IJESE), 2, pp Lenney, M., Woodcock, C., Collins, J. & Hamdi, H. (1996) The status of agricultural lands in Egypt: The use of multitemporal NDVI features derived from landsat TM. Remote Sensing of Environment, 56(1), pp. 8-20, doi: / (95) Thomann, R. & Mueller, J. (1987) Principles of Surface Water Quality Modeling and Control, HarperCollins Publishers Inc., pp & pp Varshney, A. (2013) Improved NDBI differencing algorithm for built-up regions change detection from remote-sensing data: an automated approach, Remote Sensing Letters, 4(5), pp , doi: / X