Water quality assessment of Lake Burullus, Egypt, utilizing statistical and GIS modeling as environmental hydrology applications

GIS is a very powerful tool for analyzing huge amount of data and connecting them with the geography; moreover, recently, there is great advancement in the field. The main objective of this study is to assess the water quality (WQ) and trophic status (TS) conditions of Lake Burullus, Egypt, using statistical modeling (PCA/FA and CA), WQ index (L-WQI), and trophic status index (Carlson TSI and TRIX) approaches, in addition to using GIS tools for building models able to automatically calculate the various indices and producing color coded maps for the lake. The results indicated that PCA/FA grouped the twenty-four WQ parameters into nine principal components explaining 72.6% of the total variance, domestic, and agriculture pollution were dominant. CA divided the twelve sampling stations into most and least polluted groups. The lake WQ was classified as a "Very Poor," according to L-WQI. Moreover, the results of the Carlson TSI and TRIX indices were coincided and classified the eutrophication levels in the lake as "Hyper-Eutrophic" and "Elevated Trophic," respectively. Based on the results of this study, Lake Burullus needs urgent plans for recovering its WQ. Pre-treatment for its drains' effluents and implementing of a periodical WQ monitoring program are highly recommended.

Water quality monitoring of Lake Burullus (Egypt) using Landsat satellite imageries

Lake Burullus is one of the most important coastal lakes in Egypt, as it participates with a considerable amount of fish yield in Egypt. Despite its importance, it is considered as a vulnerable lake, since it is subjected to significant environmental changes caused by various anthropogenic activities. Severe deterioration of its water quality status, as well as a decrease in its water area, has been noticed throughout the last four decades. The main objective of this study is to evaluate the ability of remote sensing for assessing the water quality status of the lake for the period from August 2010 to August 2013. Remote sensing technique was used to retrieve and predict the lake water quality parameter records through the assessment period (August 2010 to August 2013). Stepwise multi-linear regression technique was used to correlate between the field measurements of water quality parameters and the reflectance of remote sensing imageries, and then the derived models were validated. The results revealed the critical status of water quality conditions of the lake, particularly of its southern and southeastern parts. The results showed also that some water quality parameters (Chl-a, TSS, pH, Fe, Zn, Cr, and NH₄) can be retrieved from remote sensing imageries with reasonable accuracy (R² = 0.86, 0.67, 0.65, 0.63, 0.62, 0.61, and 0.6, respectively), while the water quality parameters, which can be predicted, based on calibrated and validated regression models are TSS and Chl-a, with acceptable accuracy (R² = 0.6 and 0.43, respectively). Lake Burullus needs urgent plans and strategies to protect its water quality from the potential hazards of human activities. The study proved the ability of remote sensing as an effective technique to monitor the changes in water quality conditions of shallow coastal lagoons and to predict with some water quality parameters without field measurements; therefore, it is highly recommended to be used by decision makers.

Assessment of climate change impacts on water quality parameters of Lake Burullus, Egypt

Egyptian Mediterranean coast hosts five shallow lagoons which play a vital role in the national economy. Lake Burullus is the second largest one that is located in the Nile Delta and is connected to the Mediterranean by a narrow outlet. This lagoon faces various anthropogenic-induced implications that threat its ecosystem and biodiversity. The prime objective of this study is investigating the impacts of future climate change (CC) on its characteristics. A 2-D hydro-ecological modeling for the lagoon was implemented, using MIKE21FM. The proposed model was calibrated and validated against the collected water quality records, for two successive years (2011-2013), at twelve monitoring stations throughout the lagoon. The simulations were executed for various parameters, including water depth, salinity, DO, BOD, and nutrient components. Six simulations from different regional climate models (RCMs) were obtained and examined to extract the most accurate climatic projections for the lagoon coordinates. These climatic estimates cover three Representative Concentration Pathways (RCPs) scenarios according to the IPCC's Fifth Assessment Report (AR5). A moderate sea level rise (SLR), locally projected offshore from the Nile Delta coast, was obtained. The validated model was forced with the climatic and SLR projections of 2 years representing the mid and long-term future of the twenty-first century. The model results showed that the developed model is an efficient tool to simulate the lagoon characteristics. The results of the modified model showed that CC has the potential to radically alter the physical and chemical structure of Lake Burullus. The results emphasized that the lagoon is expected to be warmer and more saline. The risk of oxygen depletion is firmly predictable with significant spatial differences of DO decreasing. A prolonged residence time is expected, accompanied by an increasing trend of phosphate and chlorophyll-a and a decreasing trend of nitrate. CC impacts on Lake Burullus should be considered in its urgently required management plan.

Change detection for Lake Burullus, Egypt using remote sensing and GIS approaches

Lake Burullus is the second largest natural coastal lake in Egypt. It has an economic importance for fish yield. However, several anthropogenic activities such as industrial, agriculture, and reclamation activities lead to a deterioration of its water quality and a decrease of the water body area of the lake. This study aims to detect the spatiotemporal changes of Lake Burullus in the period 1972-2015 using 12 Landsat {(1,3-MSS), (4,5-TM), and (7-ETM+)} imageries and water indices approach. To extract water feature from imageries, the Normalized Difference Water Index (NDWI) and the Water Ratio Index (WRI) were applied. The NDWI was applied to the MSS imageries. For other TM and ETM+ imageries, the WRI was applied. Obtained results show a significant decrease in the water area of the Lake Burullus, where it lost about (49%) of its surface area during the period from the year 1972 to the year 2015. A rapid decrease in the lake surface area was noticed through the period from 1972 to 1984. A prediction model was built depending on the calculated water area of the lake. Finally, the multi-temporal maps of the lake surface area are overlaid to produce a map for the changes of the lake surface area using Geographic Information System (GIS).