Trophic state and potential productivity assessment for Qaroun Lake using spatial techniques.

Qaroun Lake is one of the most important Egyptian lakes which, recently, have been exposed to severe degradation in water quality and fish productivity. In this manuscript, Carlson's trophic state index (CTSI) was used to evaluate the trophic state, while the trophometric index (TMI) was used to assess the potential productivity of Qaroun Lake. The present study is one of the initial attempts to investigate these indices in Qaroun Lake. To achieve this work, an integrated multidisciplinary approach was adopted integrating field investigation, geographic information system, and data analysis. CTSI combines three variables of water quality: chlorophyll-a (CHL-a), total phosphorus (TP), and transparency measured by Secchi disk depth (SDD). The result of overall CTSI showed the hypereutrophic state is represented by 62% and eutrophic state is represented by 38% of the total lake's area. Moreover, the calculated TMI indicated the average potential productivity value (PP) is 619 t. It can be concluded that the hypereutrophic is the dominant state in Qaroun Lake. The present study recommends the application of TMI model to evaluate and monitor the changes in Qaroun Lake's potential productivity in response to the changing environmental conditions and other biological pressures (e.g., Isopoda paraside).

Remote sensing and statistical analyses for exploration and prediction of soil salinity in a vulnerable area to seawater intrusion.

Soils along the Egyptian coast are vulnerable to environmental degradation and soil salinity problems. The main objective of this study is to identify and rapidly predict salt affected soils using remote sensing data and multivariate statistical analysis. To achieve this objective, the Operational Land Imager 8 (OLI) of Landsat imagery acquired in March 2022 was processed through the Maximum Likelihood classifier to assess Landscape features and to produce Normalized difference salinity index (NDSI) and normalized difference vegetation index (NDVI). Water and soil samples were collected from 13 field sites as ground truth data and to investigate representative physical and chemical properties. Linear regression model was used to predict soil salinity while soil parameters were mapped using Inverse Distance Weight (IDW) in ArcGIS 10.5. In order to explore the soil salinity content using VNIR-SWIR spectra, this work investigated the potential of Partial least squares regression (PLS regression) and SVM (Support vector machine). For simulating salinity in the investigated area, a total number of 65 different sites were identified considering that almost 75 % (50 sites) were used to develop the model and 25 % (15 sites) for validation of the established model. The results indicated that EC levels of water samples are not suitable for irrigation (> 3 mS/cm). Majority of the collected soil samples represent saline-alkaline soils. NDSI ranged from -0.83 to 0.57 with mean of -0.25. Based on the variance of components, 90 % of data were obtained from the first three PCA. The PLS model's R2 score of 0.763 and extremely low p value indicates how well it predicts soil salinity. SVM model R2, on the other hand, is 0.719. Further, Ca++ and Mg++ are the main significant parameters selected in the predicted model. This shows that remote sensing data and multivariate analysis are very important tools to map spatial variation and predict soil salinity. The developed model for salinity considered both the spectral retrieved parameters and lab analyses of cations giving higher accuracy.

Monitoring effect of nickel, copper, and zinc on growth and photosynthetic pigments of Spirulina platensis with suitability investigation in Idku Lake.

Owing to the increase of pollutant sources in oceans, seas, and lakes, there is an expected effect on growth and metabolism of planktonic algae which are considered primary producers in the ecosystem. Therefore, it becomes urgent to carry out laboratory studies to test to what extent these pollutants can affect the growth of algae which is necessary as a food for marine fishes. Spirulina is considered the most important algal species due to its high nutritional value for humans and animals. Therefore, this work investigated the effect of different concentrations of Ni2+, Zn2+, and Cu2+ metal ion pollutants on growth of the blue-green alga Spirulina platensis. EC50 was identified to be around 2 mg/l for the three heavy metals. The suitability of Idku Lake for Spirulina platensis growth was investigated using multi-criteria spatial modeling integrated with remotely sensed data processing. Spatial distribution maps of turbidity, water nutrients, and phytoplankton were the input criteria used to assess Idku Lake's suitability. The results obtained proved that low concentrations of the tested heavy metals stimulated growth and pigment fractions (chlorophyll a, carotenoids, and total phycobilins content) but to different degrees. The inhibitory effect was more prominent in the case of copper ions than zinc and nickel ions with all concentrations used. The overall suitability map of Spirulina platensis in Idku Lake showed that the whole lake is suitable for growth and proliferation except for the northwestern corner due to the high salinity levels. The present paper helps to understand the behavior of algae responding to environmental pollution, which supports environmental planners with the necessary baseline for investigating the fate of pollutants and the potential risk.

Effect of heavy metals on protein content of marine unicellular green alga Dunaliella tertiolecta.

Microalgae are rich source of protein containing necessary amino acids at different levels. The present study was designed to assess stimulatory and/or inhibitory impact of five different concentrations (5, 10, 15, 20, and 25 mg/L) of three essential heavy metals (nickel, zinc, and copper) on protein content (soluble, insoluble, and total) of the marine unicellular green alga Dunaliella tertiolecta. Further, geospatial analyses were used to assess the suitability of Qaroun Lake for D. tertiolecta proliferation. The experimental results showed a gradual increase in protein content of D. tertiolecta with low concentrations of the three investigated heavy metals. However, increasing levels of heavy metals led to inhibitory effect on protein synthesis in alga with different grades. Ni, Zn and Cu levels in Qaroun lake were found suitable for the proliferation of Dunaliella (Lower than 5 mg/L). The present study highly recommends the necessity to encourage site selection of optimal marine environments suitable for the proliferation of marine algae rich in protein content.

Environmental analysis of soil characteristics in El-Fayoum Governorate using geomatics approach.

The present study aims at identifying the impact of wastewater irrigation on soil characteristics of El-Fayoum Governorate using Landsat images and geo-statistical techniques integrated with field investigation and soil analyses. Soil samples were collected from 40 representative sites during November/December 2016 and analyzed for pH, electric conductivity (EC), organic carbon (OC), total nitrogen (TN), total phosphorus (TP), Ca, K, Na, and Mg. Landsat images were processed to produce spectral indices of water (MNDWI), vegetation (NDVI), salinity (NDSI), and urban areas (NDBI). Inverse distance weighting in ArcGIS 10.1 was used for mapping soil characteristics. Results refereed to a fluctuation in soil characteristics among different districts, as a result of variation and severity of activities. High levels of OC (3.5-5.21%) were recorded in several scattered parts while northern parts showed high levels of TP and TN recording 0.8-1.7 mg/g and 1.7-2.4 mg/g respectively. A great fluctuation in salinity, Ca, K, and Na levels were detected among the collected soil samples. Southern and eastern borders of the governorate showed high levels of Ca (> 17.7 mg/g). The most alkaline soil samples (> 8) were mostly recorded in El-Fayoum and Tamia districts. Variation of soil characteristics is greatly impacted by irrigation using wastewater particularly from El-Bats and El-Wadi drains. A strong positive correlation (0.94) was observed between urbanization (NDBI) and land salinization (NDSI) which ensures the negative impact of residential areas on agricultural lands. It can be concluded that the agricultural land problems have greatly been impacted by the lack of sufficient water supply. Geospatial techniques along with soil analyses facilitate studying such problems.