The search for target values of quality indices for bioindicators of the ecological state and environmental factors: Case study of water bodies of the Don river

2009 ◽  
Vol 36 (6) ◽  
pp. 706-717 ◽  
Author(s):  
A. P. Levich ◽  
E. A. Zaburdaeva ◽  
V. N. Maksimov ◽  
N. G. Bulgakov ◽  
S. V. Mamikhin
Keyword(s):  
Environmental Factors ◽  
Water Bodies ◽  
Ecological State ◽  
Quality Indices ◽  
Target Values ◽  
Don River

scholarly journals Influence of Anthropogenic Loads on Surface Water Status: A Case Study in Lithuania

2021 ◽  
Vol 13 (8) ◽  
pp. 4341
Author(s):  
Laima Česonienė ◽  
Daiva Šileikienė ◽  
Vitas Marozas ◽  
Laura Čiteikė
Keyword(s):  
Total Nitrogen ◽  
Water Status ◽  
Arable Land ◽  
Ecological Status ◽  
Water Bodies ◽  
Agricultural Pollution ◽  
Good Ecological Status ◽  
Water Catchment ◽  
Lake Basins

Twenty-six water bodies and 10 ponds were selected for this research. Anthropogenic loads were assessed according to pollution sources in individual water catchment basins. It was determined that 50% of the tested water bodies had Ntotal values that did not correspond to the good and very good ecological status classes, and 20% of the tested water bodies had Ptotal values that did not correspond to the good and very good ecological status classes. The lake basins and ponds received the largest amounts of pollution from agricultural sources with total nitrogen at 1554.13 t/year and phosphorus at 1.94 t/year, and from meadows and pastures with total nitrogen at 9.50 t/year and phosphorus at 0.20 t/year. The highest annual load of total nitrogen for lake basins on average per year was from agricultural pollution from arable land (98.85%), and the highest total phosphorus load was also from agricultural pollution from arable land (60%).

scholarly journals A Machine Learning Approach for Estimating the Trophic State of Urban Waters Based on Remote Sensing and Environmental Factors

2021 ◽  
Vol 13 (13) ◽  
pp. 2498
Author(s):  
Shijie Zhu ◽  
Jingqiao Mao
Keyword(s):  
Remote Sensing ◽  
Environmental Factors ◽  
Water Temperature ◽  
Trophic State ◽  
Trophic Levels ◽  
Water Bodies ◽  
Trophic State Index ◽  
Urban Water ◽  
Estimation Model ◽  
Input Variables

To improve the accuracy of remotely sensed estimates of the trophic state index (TSI) of inland urban water bodies, key environmental factors (water temperature and wind field) were considered during the modelling process. Such environmental factors can be easily measured and display a strong correlation with TSI. Then, a backpropagation neural network (BP-NN) was applied to develop the TSI estimation model using remote sensing and environmental factors. The model was trained and validated using the TSI quantified by five water trophic indicators obtained for the period between 2018 and 2019, and then we selected the most appropriate combination of input variables according to the performance of the BP-NN. Our results demonstrate that the optimal performance can be obtained by combining the water temperature and single-band reflection values of Sentinel-2 satellite imagery as input variables (R2 = 0.922, RMSE = 3.256, MAPE = 2.494%, and classification accuracy rate = 86.364%). Finally, the spatial and temporal distribution of the aquatic trophic state over four months with different trophic levels was mapped in Gongqingcheng City using the TSI estimation model. In general, the predictive maps based on our proposed model show significant seasonal changes and spatial characteristics in the water trophic state, indicating the possibility of performing cost-effective, RS-based TSI estimation studies on complex urban water bodies elsewhere.

Factors Affecting on Entrepreneurial Intention of University Students (Case Study on Wollo University)

2021 ◽  
Author(s):  
Abdu Kamil
Keyword(s):  
Environmental Factors ◽  
University Students ◽  
Family Background ◽  
Secondary Data ◽  
Entrepreneurial Intention ◽  
Primary Data ◽  
Personal Factors ◽  
Factors Affecting ◽  
College Of Business

Abstract Background: Entrepreneurship is essential in creating, fulfilling and forming a healthy economy. This study is conducted to investigate Factor Affecting on Entrepreneurial Intention: The case study on Wollo University Students. Some studies have been done in this area but only a few were conducted in Ethiopia. This research aims to address the gap that exists due to the weakness of previous studies to verify the factors that affect entrepreneurial intention and provide more clarification on the topic. Methods: For the purpose of this study explanatory research design was employed. The researcher used stratified random sampling to classify all participants into seven colleges and one school of law. From each stratum proportionally by using purposive sampling to select 226 respondents with graduate students from college of business and economics for the desire of the study. Both primary and secondary data were collected. Primary data were collected through structured questionnaire from 210 students. Secondary data were collected from previous studies and used as reference. Results: The correlation and regression analysis has been applied to see the relationship and how independent variables influence entrepreneurial intention. From the analyses it is confirmed that demographic factors have statistically insignificant effect on entrepreneurial intention, while personal factors, environmental factors and family background have a statistically significant effect on entrepreneurial intention. Conclusions: Based on the findings it is concluded that demographic factor does not affect entrepreneurial intention while personal factors, environmental factors and family background affect entrepreneurial intention.

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