ORIGINAL_ARTICLE
The relationships between meteorological parameters and air pollutants in an urban environment
Meteorological parameters play a significant role in affecting ambient air quality of an urban environment. As Dhaka, the capital city of Bangladesh, is one of the air pollution hotspot among the megacities in the world, however the potential meteorological influences on criteria air pollutants for this megacity are remained less studied. The objectives of this research were to examine the relationships between meteorological parameters such as daily mean temperature (o C), relative humidity (%) and rainfall (mm) and, the concentration of criteria air pollutants (SO2, CO, NOx, O3, PM2.5 and PM10) from January, 2013 to December, 2017. This study also focused on the trend analysis of the air pollutants concentration over the period. Spearman correlation was applied to illustrate the relationships between air pollutants concentration and temperature, relative humidity and rainfall. Multiple linear and non-linear regressions were compared to explore potential role of meteorological parameters on air pollutants' concentrations. Trend analysis resulted that concentration of SO2 is increasing in the air of Dhaka while others are decreasing. Most of the pollutants resulted negative correlation with atmospheric temperature and relative humidity, however, they showed variable response to seasonal variation of meteorological parameters. Regression analysis resulted that both the multiple non-linear and linear model performed similar for predicting concentrations of particulate matters but for gaseous pollutants both model performances were poor. This research is expected to contribute in improving the forecast accuracy of air pollution under variable meteorological parameters considering seasonal fluctuations.
https://www.gjesm.net/article_34908_c34418e18e8ee7aa9cac4245a9987f04.pdf
2019-07-01
265
278
10.22034/GJESM.2019.03.01
Air pollution
Humidity
PM2.5 and PM10
Regression Analysis
Temperature
I.
Kayes
ikayes1@lakeheadu.ca
1
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
LEAD_AUTHOR
S.A.
Shahriar
shihab0212@gmail.com
2
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
AUTHOR
K.
Hasan
kamrulh9560@gmail.com
3
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
AUTHOR
M.
Akhter
munia14090@gmail.com
4
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
AUTHOR
M.M.
Kabir
mahbubkabir556@gmail.com
5
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
AUTHOR
M.A.
Salam
s_salam@yahoo.com
6
Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
AUTHOR
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ORIGINAL_ARTICLE
Watershed conservation prioritization using geomorphometric and land use-land cover parameters
Geomorphometric features and land use/land cover are essential in the context of watershed prioritization for resources conservation and protection. Watersheds in tropical regions like the Philippines are under threat of degradation due to the combined effects of uncontrolled agricultural activities in the uplands and frequently increasing erosive precipitations brought about by climate change. Watershed managers are challenged with these pressing issues and concerns because most watersheds have no sufficient data as a basis for decision making. This paper presents the method of analyzing the different geomorphometric features and the existing land use or land cover to assess the propensity of the watershed against erosion so that areas needing immediate treatment can be prioritized. Arbitrarily, fourteen subwatersheds coded as SW1 to SW14 were delineated using a digital elevation model and geographic information system tool. Geomorphometric features categorized as areal aspect, relief features, and channel morphology parameters were generated and analyzed. Parameters having direct and inverse effect to erosion risk was used as the criteria in the ranking process. Land use/land cover was added to geomorphometric parameters to come up with compound values for final prioritization. Results showed that SW13, SW14, and SW4 were classified under very high priority implying focus for appropriate management actions while SW10, SW6, and SW7 were classified under very low priority suggesting favorable environmental condition in these areas. The study provides significant information helpful to watershed managers and planners especially in crafting a plan for integrated watershed management wherein programs and projects implementation have to be prioritized.
https://www.gjesm.net/article_34769_47aaa147f7962777b119a3e6b138e599.pdf
2019-07-01
279
294
10.22034/GJESM.2019.03.02
Digital elevation model
erosion
Geographic Information System
watershed management
G.R.
Puno
grpuno@cmu.edu.ph
1
College of Forestry and Environmental Science, Central Mindanao University, Musuan, Maramag, Bukidnon, Philippines
LEAD_AUTHOR
R.C.C.
Puno
rccpuno@gmail.com
2
College of Forestry and Environmental Science, Central Mindanao University, Musuan, Maramag, Bukidnon, Philippines
AUTHOR
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4
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67
ORIGINAL_ARTICLE
Water quality management of heavily contaminated urban rivers using water quality analysis simulation program
Precisely management of water quality in urban rivers is of significant and water environmental capacity provide a useful tool. This study presented a water quality analysis simulation program model-based approach for dynamical load reduction in Ashi River, highly contaminated tributaries of Songhua River, China. The actual and surplus dynamic environmental capacity of CODCr and NH3-N, as the two controlling endpoints, were computed based on “segment-end-control” method for monthly or seasonal management. The dynamic pollution control scheme and monthly to annual control strategies were produced based on calculated results. Results show that CODCr and NH3-N need to be cut down to approximately 462.47t/a and 5.2t/a at Zhujia-Acheng down reach and 282.42 t/a and 9.25t/a Acheng down-Chenggaozi town reach, respectively under 90% hydrological design reliability to keep the water quality at class-IV. The CODCr and NH3-N of three ditches should be strictly controlled throughout the year. Some interesting temporal-spatial characteristics of surplus environmental capacity were also found in the study. This study provides local governments with technical measurements and policy recommendations for highly contaminated water body treatment. In the future, the river water quality management in the winter season should take into particular consideration.
https://www.gjesm.net/article_35129_ffe78ef24b15be2c98c7581de9286186.pdf
2019-07-01
295
308
10.22034/GJESM.2019.03.03
Ashi River
Chemical oxygen demand
Ammonia nitrogen
Water environmental capacity
Water quality analysis simulation program (WASP)
J.
Jiang
jiangjp@sustech.edu.cn
1
School of Environmental Science and Engineering, Southern University of Science and Technology, 518055, China
LEAD_AUTHOR
T.
Ri
273417765@qq.com
2
School of Environment, Harbin Institute of Technology, Harbin, 150090, China
AUTHOR
T.
Pang
ptrhit@qq.com
3
School of Environmental Science and Engineering, Southern University of Science and Technology, 518055, China
AUTHOR
Y.
Wang
wangyuanyuan13@126.com
4
Shenyang Urban Planning Design and Research Institute, Shenyang, 110179, China
AUTHOR
P.
Wang
pwang73@hit.edu.cn
5
School of Environment, Harbin Institute of Technology, Harbin, 150090, China
AUTHOR
Afshar, A.; Masoumi F.; Solis S.S., (2018). Developing a reliability-based waste load allocation strategy for river-reservoir systems. J. Water Resour. Plann. Manage., 144(9): 04018052 (12 Pages).
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Chen, Q.W.; Wang, Q.B.; Li, Z.J.; Li, R.N., (2014). Uncertainty analyses on the calculation of water environmental capacity by an innovative holistic method and its application to the Dongjiang River. J. Environ. Sci. (Beijing, China), 26(9): 1783-1790 (8 pages).
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Dong, F.; Liu, X.B.; Peng, W.Q.; Wu, W.Q., (2014). Calculation methods of environmental capacity of surface waters: review and prospect. Adv. Water Sci., 25: 451-463 (13 pages). (in Chinese).
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Elshorbagy, A.; Teegavarapu, R. S. V.; Ormsbee, L., (2005). Total maximum daily load (TMDL) approach to surface water quality management: concepts, issues, and applications. Can. J. Civil. Eng., 32(2): 442-448 (7 pages).
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EPA-HP, (2014). Report on the State of the Environment of Heilongjiang Province, China, EPA of Heilongjiang Province (24 pages) (in Chinese).
9
Grismer, M.E., (2013). Stream sediment and nutrient loads in the Tahoe Basin-estimated vs monitored loads for TMDL "crediting". Environ. Monit. Assess., 185(9): 7883-7894 (12 pages).
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Hashemi Monfared, S.A.; Dehghani Darmian, M.; Snyder, S.A.; Azizyan, G.; Pirzadeh, B.; Azhdary Moghaddam, M., (2017). Water Quality Planning in Rivers: Assimilative Capacity and Dilution Flow. Bull. Environ. Contam. Toxicol 99: 531-541 (11 Pages).
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Huang, S.; Hesse, C.; Krysanova, V.; Hattermann, F., (2009). From meso- to macro-scale dynamic water quality modeling for the assessment of land use change scenarios. Ecol. Modell., 220(19): 2543-2558 (16 pages).
12
Li, D.H.; Jiang, J.P.; Guo, L.; Shi, B.; Wang, P.; Li, Z.F. (2016). Load Reduction of a highly contaminated river during the period of total load control pattern updating:a case study on Ashi River. Environ. Sci. Technol., 39(6): 162-167 (6 pages). (in Chinese).
13
Li, P.; Ma, F., (2012). Simulation of the COD change and parameter analysis in Songhua River Watershed. J. Harbin Inst. Technol., 44: 48-52 (5 pages). (in Chinese).
14
Liang, S.D.; Jia, H.F.; Yang, C.; Melching, C.; Yuan, Y.P., (2015). A pollutant load hierarchical allocation method integrated in an environmental capacity management system for Zhushan Bay, Taihu Lake. Sci. Total Environ., 533: 223-237 (15 pages).
15
Mahjouri, N.; Bizhani-Manzar, M., (2013). Waste Load Allocation in Rivers using Fallback Bargaining. Water Resour. Manage., 27(7): 2125-2136 (12 pages).
16
Meng, C.; Li, Y.Y.; Wang, Y.; Yang, W.; Jiao, J. X.; Wang, M.H.; Zhang, M.Y.; Li ,Y.; Wu, J.S., (2015). TMDL for phosphorus and contributing factors in subtropical watersheds of southern China. Environ. Monit. Assess., 187(8): 514 (15 pages).
17
Meng, W.; Wang, H.Y.; Wang, Y.Y., (2008). The Study on Technique of Basin Water-Quality Target Management IV: the Control-Unit-Based Effluent Permit Limits and Pollutant Reduction Technology Assessment. Res. Environ. Sci., 21(2): 1-9 (9pages). (in Chinese).
18
Meng, W.; Zhang, N.; Zhang, Y.; Zheng, B.H., (2007). The Study on Technique of Basin Water Quality Target Management I: Pollutant Total Amount Control Technique in Control Unit. Res. Environ. Sci. 20: 1-8 (8 pages). (in Chinese).
19
MEP-PRC, (2014). Report on the State of the Environment of China. Ministry of Environmental Protection of the People's Republic of China. (in Chinese).
20
Shi, T. C.; Wang, F.E.; Fang, X.B., (2010). Regional management strategy integrated with WASP model on water quality for river-network plain located in Huzhou District, Taihu Lake Basin. Acta Scien. Circum., 30(3): 631-640 (10 pages). (in Chinese).
21
Sui, M.R., (2013). Study on Water Quality Simulation and Polltant Assimulation Capacity Caculation of Harbin Section of Ashi River. Harbin Inst. Technol. (70 pages). (in Chinese).
22
The State Council, (2015). Notice of the State Council on Issuing the Action Plan for Prevention and Control of Water Pollution. (in Chinese).
23
The State Council, (2006). Written Reply of the State Council on The Total Discharge of Major Pollutants Control Plan During the Period of Eleventh Five-Year Plan. (in Chinese).
24
Wang, Y.Y.; Guo, L.; Wang, Y.; Ran, M.; Liu, J.; Wang, P., (2013). Research and Application of Pollution Control in the Middle Reach of Ashe River by Multi-Objective Optimization. J. Geosci. Environ. Protect., 01(02): 1-6 (6 pages).
25
Wei, W.L.; Zeng, S.Y.; Du, P.F.; Chen, J.N.; Liu, Y., (2014). A method for determining water pollutant discharge limit based on combination of administrative goal-oriented and environmental capacity-based total pollution load control patterns. China Environ. Sci., 34: 136-142 (7 pages) (in Chinese).
26
Wool, T.A.; Ambrose, R.B.; Martin, J.L.; Comer, E.A., (2001). Water quality analysis simulation program (WASP) Version6.0: Draft User’s Manual 2001.
27
Zhang, R.B.; Qian, X.; Yuan, X. C.; Ye, R.; Xia, B.S.; Wang, Y.L., (2012). Simulation of Water Environmental Capacity and Pollution Load Reduction Using QUAL2K for Water Environmental Management. Int. J. Environ. Res. Public Health, 9(12): 4504-4521 (18 pages).
28
Zhao, Y.; Sharma, A.; Sivakumar, B.; Marshall, L.; Wang, P.; Jiang, J.P., (2014). A Bayesian method for multi-pollution source water quality model and seasonal water quality management in river segments. Environ. Modell. Software, 57: 216-226 (11 pages).
29
Zhou, J.; Ma, Y.; Ye, Z.; Pan, B.Y.; Sun, W.G.; Li, J.; Zuo, Y. D., (2011). Load and status evaluation of agricultural non-point source pollution in Ashi River Basin. Environ. Sci. Manage., 36(5): 168-172 (5 pages) (in Chinese).
30
ORIGINAL_ARTICLE
Application of ensemble learning techniques to model the atmospheric concentration of SO2
In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and regression tree using M5 algorithm. The prediction of Sulphur dioxide was based on atmospheric pollutants and meteorological parameters. While, the model performance was assessed by using four evaluation measures namely Correlation coefficient, mean absolute error, root mean squared error and relative absolute error. The results obtained suggest that 1) homogenous ensemble classifier random forest performs better than single base statistical and machine learning algorithms; 2) employing single base classifiers within bagging as base classifier improves their prediction accuracy; and 3) heterogeneous ensemble algorithm voting have the capability to match or perform better than homogenous classifiers (random forest and bagging). In general, it demonstrates that the performance of ensemble classifiers random forest, bagging and voting can outperform single base traditional statistical and machine learning algorithms such as linear regression, support vector machine for regression and multilayer perceptron to model the atmospheric concentration of sulphur dioxide.
https://www.gjesm.net/article_35122_88cdaee6e557116a450b85b9347d60f9.pdf
2019-07-01
309
318
10.22034/GJESM.2019.03.04
Air pollution modeling
Ensemble learning techniques
Multilayer Perceptron (MLP)
Random Forest
Bagging
Sulphur dioxide (SO2)
Support Vector Machine (SVM)
Voting
A.
Masih
adven.masikh@urfu.ru
1
Department of System Analysis and Decision Making, Ural Federal University, Ekaterinburg, Russian Federation
LEAD_AUTHOR
Abdul-Wahab, S.A.; Al-Alawi, S.M.. (2002). Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks. Environ Modell Software, 17: 219-228 (10 Pages).
1
Alfaro, E.; Garcı́a, N.; Gámez, M.; Elizondo, D., (2008). Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks. Decis. Support Syst., 45: 110-122 (13 pages).
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Baawain, M.S.; Al-Serihi, A.S., (2014). Systematic approach for the prediction of ground-level air pollution (around an industrial port) using an artificial neural network. Aerosol Air Qual. Res., 14: 124-134 (11 pages).
3
Balasubramanian, V.; Ho, S.S.; Vovk, V.,(2014). Conformal prediction for relaible machine learning: theory, adoptions and applications. Newnes
4
Bedoui, S.; Gomri, S.; Samet, H.; Kachouri, A., (2016). A prediction distribution of atmospheric pollutants using support vector machines, discriminant analysis and mapping tools (Case study: Tunisia). Pollution, 2: 11-23 (13 pages).
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Brunekreef, B. and. (2002). Air pollution and health. The Lancet, 360(9341): 1233-1242 (10 pages).
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Brunelli, U.; Piazza, V.; Pignato, L.; Sorbello, F.; Vitabile, S., (2007). Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo, Italy. Atmos. Environ., 41, 2967-2995 (29 pages).
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Fathima, A.; Mangai, J.A.; Gulyani, B.B., (2014). An ensemble method for predicting biochemical oxygen demand in river water using data mining techniques. Int. J. River Basin Manage., 12: 357-366 (10 pages).
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Gabralla, L.A.; Abraham, A., (2014). Prediction of oil prices using bagging and random subspace. Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications, 343-354 (12 pages).
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15
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Lu, W.Z.; Fan, H.Y.; Lo, S.M., (2003). Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong. Neurocomputing, 51: 387-400 (14 pages).
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Lu, W.Z.; Wang, W.J.; Wang, X.K.; Xu, Z.B.; Leung, A.Y., (2003). Using improved neural network model to analyze RSP, NO x and NO 2 levels in urban air in Mong Kok, Hong Kong. Environ. Monit. Assess., 87: 235-254 (20 pages).
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Lu, W.Z.; Wang, D., (2014). Learning machines: Rationale and application in ground-level ozone prediction. Appl. Soft. Comput., 24: 135-141 (7 pages).
20
Masih, A., (2018a). Thar Coalfield: Sustainable Development and an Open Sesame to the energy security of Pakistan. IOP Conference Series: Journal of Physics, 989 (1): 012004 (8 pages).
21
Masih, A., (2018b). Modeling the atmospheric concentration of Carbon monoxide by using Ensemble Learning Techniques. Proceedings of the 5th International Young Scientists Conference on Information Technologies, Telecommunications and Control Systems, 2298: 12 (8 pages).
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Nawahda, A., (2016). An assessment of adding value of traffic information and other attributes as part of its classifiers in a data mining tool set for predicting surface ozone levels. Process Saf. Environ. Prot., 99: 149-158 (10 pages).
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Palani, S.; Liong, S.Y.; Tkalich, P., (2008). An ANN application for water quality forecasting. Mar. Pollut. Bull., 56: 1586-1597 (12 pages).
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Schlink, U.; Dorling, S.; Pelikan, E.; Nunnari, G.; Cawley, G.; Junninen, H.; Greig, A.; Foxall, R.; Eben, K.; Chatterton, T.; Vondracek, J.; Richter, M.; Dostal, M.; Bertucco, L.; Kolehmainen, L.; Doyle, M., (2003). A rigorous inter-comparison of ground-level ozone predictions. Atmos. Environ., 37: 3237-3253 (17 pages).
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33
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34
Tüfekci, P., (2014). Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. Int. J. Electr. Power Energy Syst., 60: 126-140 (15 pages).
35
Loon, M.J.W.; Vautard, R.; Schaap, M.; Bergström, R.; Bessagnet, B.; Brandt, J.; Builtjes, P.J.H.; Christensen, J.H.; Cuvelier, C.; Graff, A.; Jonson, J.E.; Krol, M.; Langner, J.; Roberts, P.; Rouil, L.; Stern, R.; Tarrasón, L.; Thunis, P.; Vignati, E.; White, L.; Wind, P., (2007). Evaluation of long-term ozone simulations from seven regional air quality models and their ensemble. Atmos. Environ., 41, 2083-2097 (15 pages).
36
Wang, D.; Lu, W.Z., (2006). Interval estimation of urban ozone level and selection of influential factors by employing automatic relevance determination model. Chemosphere, 62: 1600-1611 (12 pages).
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38
WHO, (2014). WHO's ambient air pollution database Update 2014.
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Windeatt, T., (2008). Ensemble MLP classifier design. Comput. Intell. Paradigms., 133-147 (15 pages).
40
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43
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44
ORIGINAL_ARTICLE
Remote sensing for urban heat and cool islands evaluation in semi-arid areas
Cities are experiencing rapid population growth and consequently extensive urbanization. Land-use/land-cover change is one of the important elements worldwide, which significantly affect the environment. This study aims to describe the emergence of urban heat and cool islands as a result of changes in land-use/land-cover. Land surface temperature over a 32-year period in Isfahan city, Iran was retrieved. The results confirmed the effect of land-use/land-cover change on Landsat land surface temperature. The average land surface temperature changed from 37.5°C in 1985 to 42.7°C in 2017 during August. The highest land surface temperature in the study area for both years occurred on bare soils (40.66°C in 1985 and 45.88°C in 2017). The second highest Landsat land surface temperature was recorded in central parts of the city with dense built-up covers (36.93°C in 1985 vs 42.45°C in 2017). The central parts of the city were found to have a lower Landsat land surface temperature compared to bare soils, which contributes to the formation of urban cool islands. As expected, water bodies and vegetation had a lower Landsat land surface temperature compared to other land covers. The results also showed changes in land use types during 1985 and 2017, with an increase in water bodies (148.82%) and built-up areas (39.67%) and a decrease in vegetation (20.08%) and bare soil (12.42%). The areas converted from vegetation to built-up experienced an increase in Landsat land surface temperature, which confirmed the effect of land-use/land-cover on microclimate.
https://www.gjesm.net/article_35131_f3c038e3c13f017d940748f5891bb1d5.pdf
2019-07-01
319
330
10.22034/GJESM.2019.03.05
Landsat land surface temperature (LST)
Land-use/land-cover (LULC)
Urban cool island (UCIs)
Urban heat island (UHIs)
Semi-arid areas
M.
Reisi
marzieh.reisi2@gmail.com
1
Department of Environmental Sciences, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran
LEAD_AUTHOR
M.
Ahmadi Nadoushan
m.ahmadi@khuisf.ac.ir
2
Department of Environmental Sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
AUTHOR
L.
Aye
lua@unimelb.edu.au
3
Renewable Energy and Energy Efficiency Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, VIC 3010, Australia
AUTHOR
Ahmad, F., (2012). Detection of change in vegetation cover using multi-spectral and multi-temporal information for District Sargodha, Pakistan. Soc. Nat., 24(3): 557-571 (15 pages).
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Al-Ali, A.; Mubarak, H., (2015). The effect of land cover on the air and surface urban heat island of a desert Oasis. Ph.D., Durham University.
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4
Alavipanah, S.; Wegmann, M.; Qureshi, S.; Weng, Q.; Koellner, T., (2015). The role of vegetation in mitigating urban land surface temperatures: A case study of Munich, Germany during the warm season. Sustainability,7(4): 4689-4706 (18 pages).
5
Amanollahi, J.; Tzanis, C.; Ramli, M. F.; Abdullah, A. M., (2016). Urban heat evolution in a tropical area utilizing Landsat imagery. Atmos. Res., 167: 175-182 (8 pages).
6
Bai, L.; Woodward, A.; Liu, Q., (2016). County-level heat vulnerability of urban and rural residents in Tibet, China. J. Environ. Health., 15(1): 3-13 (11 pages).
7
Barsi, J. A.; Schott, J. R.; Hook, S. J.; Raqueno, N. G.; Markham, B. L.; Radocinski, R. G., (2014). Landsat-8 thermal infrared sensor (TIRS) vicarious radiometric calibration. Remote Sens., 6(11): 11607-11626 (20 pages).
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Bogoliubova, A.; Tymków, P., (2014). Accuracy assessment of automatic image processing for land cover classification of ST. Petersburg protected area. Geodesia et Descriptio Terrarum, 13(1-2): 5-22 (18 pages).
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Butt, A.; Shabbir, R.; Ahmad, S. S.; Aziz, N., (2015). Land use change mapping and analysis using remote sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. Egypt. J. Remote Sens. Space Sci., 18(2): 251-259 (9 pages).
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Carlson, T.; Augustine, J.; Boland, F., (1977). Potential application of satellite temperature measurements in the analysis of land use over urban areas. Bull. Am. Meteorol. Soc., 1301-1303 (3 pages).
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Charabi, Y.; Bakhit, A., (2011). Assessment of the canopy urban heat island of a coastal arid tropical city: The case of Muscat, Oman. Atmos. Res., 101(1-2): 215-227 (13 pages).
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Chen, F.; Yang, X.; Zhu, W., (2014). WRF simulations of urban heat island under hot-weather synoptic conditions: The case study of Hangzhou City, China. Atmos. Res., 138: 364-377 (14 pages).
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Clinton, N.; Gong, P., (2013). MODIS detected surface urban heat islands and sinks: Global locations and controls. Remote Sens. Environ., 134: 294-304 (11 pages).
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Cui, Y. Y.; De Foy, B., (2012). Seasonal variations of the urban heat island at the surface and the near-surface and reductions due to urban vegetation in Mexico City. J. Appl. Meteorol. Climatol., 51(5): 855-868 (14 pages).
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Dong, F.; Chen, J.; Yang, F., (2018). A Study of Land Surface Temperature Retrieval and Thermal Environment Distribution Based on Landsat-8 in Jinan City. Conf. Ser.: Earth Environ. Sci., 118 (11 pages).
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Gebeyehu Admasu, T., (2017). Monitoring trends of greenness and LULC (land use/land cover) change in Addis Ababa and its surrounding using MODIS time-series and LANDSAT Data. Master of Science, Lund University. Sweden.
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Georgescu, M.; Moustaoui, M.; Mahalov, A.; Dudhia, J., (2011). An alternative explanation of the semiarid urban area “Oasis Effect”. J. Geophys. Res. D: Atmos., 116(D24). (13 pages).
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56
ORIGINAL_ARTICLE
Pollutant removal by Canna Generalis in tropical constructed wetlands for domestic wastewater treatment
Constructed wetlands have not been commonly used in Vietnam due to the lack of information in the selection of proper types of constructed wetlands, type of reeds, design parameters and performance efficiency, in tropical climates. This paper focuses on Canna generalis, which is a common reed and easy to grow both in water and wet land conditions. Two kinds of hybrid constructed wetlands were employed, including Facultative pond combined with free water sub-surface constructed wetlands system and horizontal subsurface flow combined with Aerobic pond system. It was found that the ponds played an important role in the hybrid system performance and enhanced the performance of constructed wetlands. The pollutant removal efficiencies of the hybrid systems were all higher than the single constructed wetlands. The BOD5, TSS, NH4-N and PO4-P removal efficiencies averaged 81%, 85%, 93% and 77%, respectively for the hybrid horizontal subsurface flow constructed wetlands system operated at a hydraulic loading rate of 0.075 m/day, while they were 89%, 97%, 97%, and 68%, respectively for the hybrid free water sub-surface constructed wetlands system operated at a hydraulic loading rate of 0.1 m/day. The removal rate constants (kBOD5, kNH4-N, kPO4-P) of the experimental hybrid constructed wetlands were similar to those in previous studies. However, these constants were higher for the hybrid free water subsurface constructed wetlands because of the modified structure flow of the free water subsurface constructed wetlands applied in this study, compared to conventional ones, as well as the additional benefits of the ponds in the hybrid systems.
https://www.gjesm.net/article_35321_dc150b14811afe228b6bea1bcc85228f.pdf
2019-07-01
331
344
10.22034/GJESM.2019.03.06
Canna Generalis
Constructed wetlands (CW)
Free water subsurface (FWS)
Hybrid system
Kinetic constant
Pollutant Removal
H.D.
Tran
hatd@nuce.edu.vn
1
Department of Water Supply and Sanitation, Faculty of Environmental Engineering, National University of Civil Engineering, Vietnam
LEAD_AUTHOR
H.M.T.
Vi
huonganhtn@gmail.com
2
Department of Environmental Engineering, Thai Nguyen University, Tan Thinh Ward, Thai Nguyen, Vietnam
AUTHOR
H.T.T.
Dang
huyendtt@nuce.edu.vn
3
Department of Water Supply and Sanitation, Faculty of Environmental Engineering, National University of Civil Engineering, Vietnam
AUTHOR
R.M.
Narbaitz
narbaitz@uottawa.ca
4
Department of Civil Engineering, University of Ottawa, 161 Louis Paster Pvt., Ottawa k1N 6N5, Canada
AUTHOR
Du, L.; Chen, Q.; Liu, P.; Zhang, X.; Wang, H.; Zhou, Q.; Xu, D.; Wu, Z., (2017). Phosphorus Removal Performance and Biological Dephosphorization Process in Treating Reclaimed Water by Integrated Vertical-Flow Constructed Wetlands (IVCWs). Bioresour. Technol. 243: 204-211 (8 Pages).
1
Huang, J.; Cai, W.; Zhong, Q.; Wang, S., (2013). Influence of temperature on micro-environment, plant ecophysiology and nitrogen removal effect in subsurface flow constructed wetland. Ecol. Eng. 60: 242–248 (7 pages).
2
Huang, J.; Wang, S.; Yan, L.; Zhong, Q., (2010). Plant photosynthesis and its influence on removal efficiencies in constructed wetlands. Ecol. Eng. 36: 1037–1043 (7 pages).
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Jones, R.D; Hood, M.A., (1980). Effect of Temperature, pH, Salinity and Inorganic nitrogen on the rate of ammonium oxidation by nitrifiers isolated from wetlands environment. Microb. Ecol. 6: 339-347 (9 pages).
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5
Kadlec, R.H.; Wallace, S.D., (2008). Treatment Wetlands, 2nd Edition. CRC Press, Boca Raton, Florida.
6
Kadlec, R.H., (2009). Comparison of free water and horizontal subsurface treatment wetlands, Ecol. Eng. 35: 159–174 (15 pages).
7
Kayombo, S.; Mbwette, T.; Katima, J.; Ladengaard N.; Jorgensen S., (2004). Waste Stabilization Ponds and Constructed Wetlands Design Manual. Dar es Salaam, TZ/Copenhagen, DK: UNEP-IETC/Danida (59 pages).
8
Kim, D.G.; Park, J.; Lee, D.; Kang, H., (2011). Removal of nitrogen and phosphorus from the effluent of a secondary wastewater treatment plant using a pond-marsh wetland system. Water Air Soil Pollut. 214(1): 37-47 (11 pages).
9
Konnerup, D., Koottatep, T., Brix, H., (2009). Treatment of domestic wastewater in tropical, subsurface flow constructed wetlands planted with Canna and Heliconia. Ecol. Eng. 35 (2): 248–257 (9 pages).
10
Ngo, T.D.T.; Konnerup, D.; Schierup, H.-H.; Nguyen, H.C.; Le, A.T.; Brix H., (2010). Kinetics of pollutant removal from domestic wastewater in a tropical horizontal subsurface flow constructed wetland system: Effects of hydraulic loading rate”, Ecol. Eng. 36: 527–535 (9 pages).
11
Piwpuan, N.; Jampeetong, A.; Brix, H., (2014). Ammonium tolerance and toxicity of Actinoscirpus grosses – A candidate species for use in tropical constructed wetland systems. Ecotox. Environ. Safe. 107: 319–328 (10 pages).
12
Ojoawo, S. O.; Udayakumar, G.; Naik, P., (2015). Phytoremediation of Phosphorus and nitrogen with Canna x generalize Reeds in Domestic Wastewater through NMAMIT Constructed Wetland. Aquat. Procedia 4:349 – 356 (8 pages).
13
Shitu, A.; Izhar, S.; Tahir, T.M., (2015). Sub-critical water as a green solvent for the production of valuable materials from agricultural waste biomass: A review of recent work. Global J. Environ. Sci. Manage., 1(3): 255-264 (10 pages).
14
Singh, S.; Haberl, R.; Moog, O.; Shrestha, R.R.; Shrestha, P.; Shrestha, R., (2009). Performance of an anaerobic baffled reactor and hybrid constructed wetland treating high-strength wastewater in Nepal-a model for DEWATs. Ecol. Eng. 35: 654-660 (7 pages).
15
Tran, D.H., (2006). Urban Wastewater treatment, 1st Edition. Science and Engineering Publisher, Hanoi.
16
USEPA, (2000). Manual constructed wetlands treatment of municipal wastewaters- National Risk Management Research Laboratory, Office of Research and Development, U.S.Environmental Protection Agency, Cincinnati, Ohio 45268-EPA/625/R-99/010.
17
Vohla, C.; Kõiv, M.; Bavor, H.J.; Chazarenc, F.; Mander Ü., (2011). Filter materials for phosphorus removal from wastewater in treatment wetlands—a review. Ecol. Eng. 37: 70-89 (10 pages).
18
Vymazal, J., (2007). Removal of nutrients in various types of constructed wetlands. Sci. Total Environ. 380: 48-65 (8 pages).
19
Vymazal J.; Kropfelová, L., (2008). A three-stage experimental constructed wetland for treatment of domestic sewage: First 2 years of operation. Ecol. Eng. 37 (2011): 90–98 (9 pages).
20
Vymazal, J., (2009). The use constructed wetlands with the horizontal sub-surface flow for various types of wastewater. Ecol. Eng. 35 (1): 1–17 (18 pages).
21
Watson, J.T.; Reed, S.C.; Kadlec, R.H.; Knight, R. L.; Whitehouse A.E., (1989). Constructed Wetlands for Wastewater Treatment, Ed. DA Hammer, Lewis Publishers, CRC Press, Boca Raton, Florida.
22
Wen, Y.; Chen, Y.; Zheng, N.; Yang, D.; Zhou, Q., (2010). Effects of plant biomass on nitrate removal and transformation of carbon sources in subsurface-flow constructed wetlands. Bioresour. Technol. 101: 7286–7292 (7 pages).
23
World Bank. 2013. Vietnam Urban Wastewater Review. Washington, DC. © World Bank.
24
Yigitcanlar, T.; Dizdaroglu, D., (2015). Ecological approaches in planning for sustainable cities: A review of the literature. Global J. Environ. Sci. Manage. 1(2):159-188 (30 pages).
25
Zhang, D.Q.; Gersberg, R.M.; Tan, S.K., (2009). Constructed wetlands in China. Ecol. Eng. 35: 1367–1378 (12 pages).
26
Zhang, D.Q.; Tan, S.K.; Gersberg, R.M.; Zhu, J.F.; Sadreddini, S.; Li, Y.F., (2012). Nutrient removal in tropical subsurface flow constructed wetlands under batch and continuous flow conditions. J. Environ. Manage. 96: 1-6 (6 pages).
27
Zhang, D.Q.; Jinadasa, K.; Gersberg, R. M.; Liu, Y.; Ng, W. J.; Tan, S.K., (2014). Application of constructed wetlands for wastewater treatment in developing countries: A review of recent developments (2000-2013). J. Environ. Manage. 141: 116-131 (16 pages).
28
Zurita, F.; De Anda, J.; Belmont, M.A., (2009). Treatment of domestic wastewater and production of commercial flowers in vertical and horizontal subsurface-flow constructed wetlands. Ecol. Eng. 35 (5): 861–869 (9 pages).
29
ORIGINAL_ARTICLE
Assessment of Guinea Savanna River system to evaluate water quality and water monitoring networks
The analysis of changes in water quality in a monitoring network system is important because the sources of pollution vary in time and space. This study utilized analysis of the water quality index calculation, hierarchical cluster analysis, and mapping. This was achieved by assessing the water quality parameters of the samples collected from Galma River in Zaria, Northwestern Nigeria in wet and dry seasons. The Analysis shows that sampling point number 15 located downstream of the river has the largest number of water quality index of 105.77 and 126.34, while sampling points 1 located upstream of the river has 62.71 and 78.09 in both wet and dry seasons respectively. This indicates that all the monitoring sites were polluted and the water could be utilized for industrial and irrigation specified due to the purposes only. Hierarchical cluster analysis and mapping revealed consistency and variations. For both networks, cluster 1 is located in the middle of the river watershed, while clusters 2, 3 and 4 show variations within the river watershed. 3 sampling points in wet season located at the upstream of the river were specified for Irrigation and Industrial uses, while the rest of the sampling points in both seasons were specified for irrigation purpose only. From this study, water quality index and multivariate techniques for environmental management can be employed in monitoring river resources, and research of this kind can help inadequate planning and management of the river system.
https://www.gjesm.net/article_35322_67141ad3a732b5d9ccfc1aeaca4521d1.pdf
2019-07-01
345
356
10.22034/GJESM.2019.03.07
Hierarchical cluster analysis (HCA)
Galma River
Mapping
statistical analysis
Water Quality Index (WQI)
G.A.
Aliyu
gadaf.loveu@gmail.com
1
Department of Environmental Science, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400, Selangor, Malaysia
AUTHOR
N.R.B.
Jamil
norrohaizah@upm.edu.my
2
Department of Environmental Science, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400, Selangor, Malaysia
LEAD_AUTHOR
M.B.
Adam
bakri@upm.edu.my
3
Faculty of Science, Universiti Putra Malaysia, 43400 Serdang, Malaysia
AUTHOR
Z.
Zulkeflee
zufarzaana@upm.edu.my
4
Department of Environmental Science, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400, Selangor, Malaysia
AUTHOR
Animesh, A.; Saxena, M., ( 2011). Assessment of pollution by physicochemical water parameters using regression analysis: A case study of Gagan River at Moradabad India. Adv. Appl. Sci. Res., 2(2): 185 -189 (5 pages).
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43
ORIGINAL_ARTICLE
Potable groundwater analysis using multivariate Groundwater Quality Index technique
In the current study, the qualitative status of potable well water was assessed using the groundwater quality index during a course of 4 years (2014-2017). This study was carried out with an aim to monitor the drinking water resources from 12 potable wells on the multivariate analysis basis and for determination of groundwater quality index, the following 13 physicochemical parameters including electrical conductivity, total dissolved solids, pH, total hardness, potassium, fluoride, bicarbonate, chloride, calcium, magnesium, sulphate, and nitrate were used. On the basis of Piper diagram, the results revealed that the type and faces of samples were chloride-sodic and bicarbonate-sodic respectively. Groundwater quality index level in the potable well water of case study area was 42.89 to 56.58 and zone water was in the good and medium range. Besides, 66.7% of the wells were in the good range and 33.3% of wells were in the medium range of water quality index. In this study, potassium and fluoride level in all the zone wells was lower than the ideal level and the electrical conductivity, total dissolved solids, sodium, magnesium and sulphate in all the wells was higher than the ideal range for drinking purposes. Based on this study results, the potable water quality of most of the study area wells generally in 2017 vis-à-vis 2014 had reduced and its main reason was the presence of geology formations, agricultural runoffs and absorbing wells in this zone.
https://www.gjesm.net/article_35515_60ad5fdc9923fac3d0b6877fe1545e30.pdf
2019-07-01
357
370
10.22034/GJESM.2019.03.08
Groundwater Quality index
Hydrochemical
Potable water quality
pollutant water
World Health Organization (WHO)
I.
Fayaji
ifayaji@yahoo.com
1
Department of Environmental Sciences, School of Natural Resources and Environment, Birjand, University of Birjand, Birjand, Iran
AUTHOR
M.H.
Sayadi
mh_sayadi@yahoo.com
2
Department of Environmental Sciences, School of Natural Resources and Environment, Birjand, University of Birjand, Birjand, Iran
LEAD_AUTHOR
H.
Mousazadeh
hodamousazadeh@gmail.com
3
Regional Water Company of South Khorasan, Birjand, Iran
AUTHOR
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Martínez-Bastida, J.J.; Arauzo, M.; Valladolid, M., (2010). Intrinsic and specific vulnerability of groundwater in central Spain: the risk of nitrate pollution. Hydrogeol. J. 18: 681–698 (18 pages).
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Moussa, A.B.; Zouari, K.; Oueslati, N., (2009). Geochemical study of groundwater mineralization in the grombalia shallow aquifer, north-eastern Tunisia: implication of irrigation and industrial wastewater accounting. Environ. Geol., 58(3): 555-566 (12 pages).
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Muhammad, S.; Tahir Shah, M.; Khan, S., (2011). Health risk assessment of heavy metals and their source apportionment in drinking water of Kohistan region, northern Pakistan. Microchem. J., 98: 334-343 (10 pages).
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Pazand, K.; Hezarkhani, A., (2013). Hydrogeochemical processes and chemical characteristics around Sahand Mountain, NW Iran. Appl. Water Sci., 3: 479–489 (11 pages).
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Ramakrishnaiah, C.R.; Sadadhiv C.; Rangnna, G., (2009). Assessment of water quality index for the groundwater in Tumkur Taluk, Karnataka State, India. E-J. Chem., 6(2): 523-530 (8 pages).
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28
Sayadi, M. H.; Rezaei, M. R.; Rezaei, A., (2015). Fraction distribution and bioavailability of sediment heavy metals in the environment surrounding MSW landfill- a case study Qayen city, Iran. Environ. Monit. AAssess., 187: 4110 (11 pages).
29
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30
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31
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40
ORIGINAL_ARTICLE
Ecological niche modeling of invasive alien plant species in a protected landscape
Non-native plants that can cause adverse effects are otherwise known as invasive alien plant species which pose a major threat to plant biodiversity conservation and sustainability. This study is dedicated to determine the plant diversity and to assess the vulnerability of Quezon Protected Landscape, Southern Luzon, the Philippines to invasive alien plant species. Data from 90 10x10 m randomly established plots using the quadrat method showed that there are 318 plant species wherein 208 are native, 100 are non-native, and 10 are invasive. Results from the association of the physicochemical factors and the presence of invasive alien plant species through Spearman rho test revealed that most of the physicochemical factors have significant association except percent slope and hill shade. Soil pH, aspect and number of non-native plants show positive association while soil moisture, leaf litter thickness, elevation, species richness, species evenness, plot species diversity index, and the number of native plants signify negative association. Differences between the plots of with and without invasive alien plant species in physicochemical factors indicate that most of the physicochemical factors have a significant difference between plots of with and without invasive alien plant species except percent slope, hill shade, and aspect. Lastly, the MaxEnt model exemplifies that the most suitable predicted conditions for invasive alien plant species are at the edges of boundary and buffer zones. This study implies that most of the physicochemical factors are linked to the presence of invasive alien plant species and Quezon Protected Landscape has a low vulnerability to invasive alien plant species invasion.
https://www.gjesm.net/article_35513_8a0e1e8c9984cb5da82f130af18ef75a.pdf
2019-07-01
371
382
10.22034/GJESM.2019.03.09
Invasive alien plant species (IAPS)
Maxent model
physicochemical factors
Quezon Protected Landscape (QPL)
Species distribution modelling (SDM)
G.C.B.
Paclibar
gicel_christine08@yahoo.com
1
College of Arts and Sciences, Lyceum of the Philippines University-Cavite, General Trias, Cavite, Philippines
LEAD_AUTHOR
E.R.
Tadiosa
gcbpaclibar@gmail.com
2
College of Science and Computer Studies-Graduate Studies, De La Salle University-Dasmarinas, Cavite, Philippines
AUTHOR
Borja, V.G.L.; Magcale-Macandog, D.B.; Lambio, I.A.F.; Brandl, R.; Hotes, S.; Settele, J.; Wiemers, M., (2015). Spatial patterns and plant species associations of coffee (Coffea spp.) along the eastern slopes of Mount Makiling Forest Reserve, Luzon, Philippines.
1
Brown, R.; Siler, C.D.; Oliveros, C.H.; Esselstyn, J.H.; Diesmos, A.C.; Hosner, P.A.; Linkem, C.W.; Barley, A.J.; Oaks, J.R.; Sanguila, M.B.; Welton, L.J.; Blackburn, D.C.; Moyle, R.G.; Peterson, A.T.; Alcala, A.C., (2013). Evolutionary diversification of vertebrates in the Philippines. Annu. Rev. Ecol. Evol. Syst. 44: 411-435 (25 pages).
2
Bunyan, M.; Bardhan, S.; Jose, S., (2015). Effect of topography on the distribution of tropical montane forest fragments: a predictive modelling approach. J. Trop. For. Sci. 27(1): 30-38 (9 pages).
3
CBD, (2009). Invasive alien species: a threat to biodiversity. Convention on Biological Diversity. 413 St. Jacques Street, Suite 800, Montreal, Quebec, Canada H2Y 1N9.
4
Cheney, C.; Esler, K.J.; Foxcroft, L.C.; van Wilgen, N.J.; McGeoch, M.A., (2018). The impact of data precision on the effectiveness of alien plant control programmes: a case study from a protected area. Biol. Invasions. 20(11): 3227-3243 (17 pages).
5
Codilla, L.T.; Metillo E.B., (2011). Distribution and abundance of the invasive plant species Chromolaena odorata L. in the Zamboanga Peninsula, Philippines. Int. J. Environ. Sci. Dev. 2(5): 406-410 (5 pages).
6
Dagamac, N.H.A.; Rea-Maminta, M.A.D.; dela Cruz, T.E.E., (2014). Plasmodial slime molds of a tropical karst forest, Quezon National Park, the Philippines. Pacific Sci., 69(3): 1-22 (22 pages).
7
Dainese, M.; Kuhn, I.; Bragazza, L., (2014). Alien plant species distribution in the European Alps: influence on species’ climatic requirements. Biol. Invasions. 16: 815-831 (17 pages).
8
DENR CALABARZON, (2013). Quezon Protected Landscape. Department of Environment and Natural Resources-Region IV-A CALABARZON.
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Dickey, J.W.E.; Cuthbert, R.N.; Rea, M.; Laverty, C.; Crane, K.; South, J.; Briski, E.; Chang, X.; Coughlan, N.E.; MacIsaac, H.J.; Ricciardi, A.; Riddell, G.E.; Xu, M.; Dick, J.T.A., (2018). Assessing the relative potential ecological impacts and invasion risks of emerging and future invasive alien species. NeoBiota. 40:1-24 (24 pages).
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EEA, (2012). The impacts of invasive alien species in Europe. European Environment Agency. European Union. ISSN 1725-2237.
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European Commission, (2013). Science for environment policy thematic issue: invasive alien species. September 2013 Issue 41.
12
Foxcroft, L.C.; Spear, D.; van Wilgen, N.J.; McGeoch, M.A., (2018). Assessing the association between pathways of alien plant invaders and their impacts in protected areas. Neobiota 43: 1-25 (25 pages).
13
ISSG, (2005). Introduction to invasive alien species. Invasive Species Specialist Group.
14
Joshi, R.C., (2006). Invasive alien species (IAS): concerns and status in the Philippines. Philippine Rice Research Institute (PhilRice).
15
Katsanevakis, S.; Wallentinus, I.; Zenetos, A.; Leppakoski, E.; Cinar, M.E.; Ozturk, B.; Grabowski, M.; Golani, D.; Cardoso, C., (2014). Impacts of invasive alien marine species on ecosystem services and biodiversity: a pan-European review. Aquat. Invasions 9(4): 391-423 (33 pages).
16
Keong, C.Y., (2015). Sustainable resource management and ecological conservation of mega-biodiversity: the Southeast Asian big-3 reality. Int. J. Environ. Sci. Dev. 6(11):876-882 (7 pages).
17
Kumschick, S.; Gaertner, M.; Vila, M.; Essl, F.; Jeschke, J.M.; Pysek, P.; Ricciardi, A.; Bacher, S.; Blackburn, T.M.; Dick, J.T.A.; Evans, T.; Hulme, P.E.; Kuhn, I.; Mrugala, A.; Pergl, J.; Rabitsch, W.; Richardson, D.M.; Sendek, A.; Winter, M., (2014). Ecological impacts of alien species: quantification, scope, caveats, and recommendations. Bioscience 65: 55-63 (9 pages).
18
Masters, G.; Norgrove, L., (2010). Climate change and invasive alien species. CABI working paper 1.
19
McNeely, J.A., (2001). The great reshuffling: human dimensions of invasive alien species. IUCN, Gland, Switzerland and Cambridge, UK.
20
McNeely, J.A.; Mooney, H.A.; Neville, L.E.; Schei, P.; Waage, J.K., (2001). A Global Strategy on Invasive Alien Species. IUCN Gland, Switzerland, and Cambridge, UK.
21
Nijs, I.; Verlinden, M.; Meerts, P.; Dassonville, N.; Domken, S.; Triest, L.; Mahy, G., (2012). Biodiversity impacts of highly invasive plants: mechanisms, enhancing factors and risk assessment. Science for a Sustainable Development (SSD). Belgian Science Policy Avenue Louise 231, Brussels, Belgium.
22
Panetta, D.; Gooden, B., (2017). Managing for biodiversity: impact and action thresholds for invasive plants in natural ecosystems. NeoBiota. 34: 53-66 (14 pages). Peerson, G.A.; Weerd, M.V., (2006). Biodiversity and natural resource management in Insular Southeast Asia. Island Stud. J., 1(1): 81-108 (28 pages).
23
PTFCF, (2015). Status of Philippine Forests. Philippine Tropical Forest Conservation Foundation, Inc.
24
Pysek, P.; Jarosik, V.; Hulme, P.E.; Pergl, J.; Hejda, M.; Schaffner, U.; Vila, M., (2012). A global assessment of invasive plant impacts on resident species, communities and ecosystems: the interaction of impact measures, invading species' traits and environment. Global Chang Biol., 18(5): 1725–1737 (13 pages).
25
Reaser, J.K.; Meyerson, L.A.; Cronk, Q.; de Poorter, M.; Elrege, L.G.; Green, E.; Kairo, M.; Latasi, P.; Mack, R.N.; Mauremootoo, J.; O’Dowd D.; Orapa, W.; Sastroutomo, S.; Saunders, A.; Shine, C.; Thrainsson, S.; and Vaiutu, L., (2007). Ecological and Socioeconomic Impacts of Invasive Alien Species in Island Ecosystems. Environ. Conserv., 34(2): 1-14 (14 pages).
26
Schlaepfer, M.A.; Sax, D.F.; Olden, J.D., (2010). The potential conservation value of non-native species. Conserv. Biol., 25(3): 428-437 (10 pages).
27
Schultheis, E.H.; MacGuigan, D.J., (2018). Competitive ability, not tolerance, may explain success of invasive plants over natives. Biol. Invasions. 20(10): 2793-2806 (14 pages).
28
Smith, R.L.; Smith, T.M. (2004). Elements of ecology. 9th Edition. Pearson Education South Asia PTE Ltd. 251-374 (124 pages).
29
Steinbauer, M.J.; Irl, S.D.H.; Gonzalez-Mancebo, J.M.; Breiner, F.T.; Hernandez-Hernandez, R.; Hopfenmuller, S.; Kidane, Y.; Jentsch, A.; Beierkuhnlein, C., (2017). Plant invasion and speciation along elevational gradients on the oceanic island La Palma, Canary Islands. Ecol Evol. 7(2): 771–779 (9 pages).
30
Tadiosa, E.R.; Santos, J.M.; Cudiamat, M.A.; Cruzate, S.M.; Arma, E.J.M.; Hilapo, D.C.G.; Biscocho, H.H., (2016). Analysis of the forest and grassland vegetation at Southwestern side of Quezon Protected Landscape, Southern Luzon, Philippines. Int. Assoc. Multidiscip. Res., 19: 53-69 (17 pages).
31
Theorides, K.A.; Dukes, J.S., (2007). Plant invasion across space and time: factors affecting nonindigenous species success during four stages of invasion. New Phytol., 176: 256-273 (18 pages).
32
Wamelink, W.; van Dobben, H.F.; Goedhart, P.W.; Jones-Walters, L.M., (2018). The Role of Abiotic Soil Parameters as a Factor in the Success of Invasive Plant Species. Emerging Sci. J., 2(6).
33
ORIGINAL_ARTICLE
Erodibility and sedimentation potential of marly formations at the watershed scale
Grupi and Kashkan marl formations comprise a considerable part of Zagros region. These formations have a considerable erodibility and sedimentation potential because of their special geological and mineralogical characteristics. The objective of this study was to compare the erosion and sediment yield of Kashkan and Grupi formations in Merk watershed located in southeast Kermanshah, using the Modified Pacific Southwest Inter-Agency Committee model. This model is suitable for estimating erosion and sediment intensity within each geomorphologic unit comprising nine effective environmental factors as geological, pedological, climate, runoff, topography, land cover, land use, surface, and river erosion factors. The results indicated that Kashkan formation comprises siltstone, sandstone, shale, and conglomerate, and Grupi formation contains shale, clay, and limestone with a high erodibility potential. Field measurements and soil samples analyzed for effective factors releaved that sediment yield for Merek watershed was 18080.6 m3/ha/y. Furthermore, field measurement and soil samples analyzed for effective factors releaved that sediment yields for Kashkan and Gurpi were 7243.3 and 10837.5 m3/ha/y, respectively. The reasons for erosion intensity and sedimentation in the two mentioned formations are slopes, vegetation and land use in addition to the type of rocks in Kashkan and Gurpi formations which are predominantly marl and shale.
https://www.gjesm.net/article_34766_bc2882aec75977f621fcd5b9005dae8c.pdf
2019-07-01
383
398
10.22034/GJESM.2019.03.10
Erosion, Gurpi formation
Kashkan formation
Kermanshah
Merk watershed
F.
Rostami
fereshtehrostami867@yahoo.com
1
Department of Geology, Sciences and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
S.
Feiznia
sfeiz@ut.ac.ir
2
Department of Range and Watershed Management, Faculty of Natural Resources, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
LEAD_AUTHOR
M.
Aleali
aleali.mohsen@gmail.com
3
Department of Geology, Sciences and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
M.
Heshmati
heshmati46@gmail.com
4
Soil Conservation and Watershed Management Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Kermanshah, Iran
AUTHOR
B.
Yousefi yegane
bizhan.yegane@gmail.com
5
Department of Geology, Faculty of Science, Lorestan, University, Khoram Abad, Iran
AUTHOR
Abdolahzadeh, A.; Ownegh, M.; Sadoddin, A.; Mostafazadeh, R., (2017). Comparison of two landslide-prone area determination methods in Ziarat Watershed, Golestan Province. J. Emergency Manage. 5(1): 5-13 (9 pages).
1
Abedian, S.; Salman Mahiny, A.; Karbakhsh Ravori, H., (2017). Estimating of erosion and sediment yield of Gorganrud basin using erosin potential method. Nat. Environ. Change 3(1): 19-32 (14 pages).
2
Altin, T., (2009). Pleistocene and Holocene fluvial development of the Ecemis Valley. Central Anatolia, Turkey, Q. Int., 204(1-2): 76-83 (8 pages).
3
Asghari Saraskanroud, S; Zeinali, B; Mohammadnejad, V., (2017). Analysis physical and chemical properties of soil and morphometric impacts on gully erosion. Desert 22-2: 157-166 (9 pages).
4
Bagherzadeh, A.; Mansouri Daneshvar, M.A., (2013). Evaluation of sediment yield and soil loss by the MPSIAC model using GIS at Golestan watershed, northeast of Iran. Arabian J. Geosci. 6, 3349-3362 (13 pages).
5
Bakker, M.M; Govers, G; Rounsevell, M.D., (2004). The crop productivity-erosion relationship: an analysis based on experimental work. Catena, 57: 55–76 (22 pages).
6
Borchardt, G., (1989). Smectites, in: Bighman, J.M.; Dixon, J.B.; Milford, M.H.; Roth, C.B.; Weed, S.B. (Eds.), Minerals in Soil Environments. Soil Sci. Soc. Am., Madison, Washington, 728-767 (40 pages).
7
Brown, A.G.; Carey, C.; Erkens, G.; Fuchs, M.; Hoffmann, T.; Macaire, J.J.; Moldenhauer, K.M.; Walling, D.E., (2009). From sedimentary records to sediment budgets: multiple approaches to catchment sediment flux. Geomorphology, 108 (1-2): 35-47 (12 pages).
8
Booij, M.J., (2005). Impact of climate change on river flooding assessed with different spatial model resolutions. J. Hydrol. 303: 176-198 (20 pages).
9
Canga, M.R., (1999). Effects of subsequent simulated rainfall on runoff and erosion. Turk. J. Agric. For. 23:659-665 (6pages).
10
Carter, M.R.; Gregorich, E.G., (2008). Soil sampling and methods of analysis, CRC Press, Taylor and Francis Group (198pages).
11
Cerda, A., (2002). The effect of season and parent material on water erosion on highly eroded soil in eastern Spain. J. Arid. Environ. 52: 319-337 (19 pages).
12
Conforti, M.; Aucelli, P.C.; Robustelli, G.; Scarciglia, F., (2011). Geomorphology and GIS analysis for mapping gully erosion susceptibility in Turbolo stream Cat chment. Northern Calabria, Italy, Nat. Hazards., 56: 881- 898 (18 pages).
13
Daneshfaraz, R.; Rahmati, M.; Akbari Moghanjiq, P., (2017). Soil erosion and sediment mapping in Aidoghmoush watershed appling MPSIAC model and GIS and RS technologies. Environ. Resour. Res. 5: 35-49 (14 pages).
14
Ekwu, E.I.; Harrilal, A., (2010). Effect of soil type, peat, slope, compaction effort and their interactions on infiltration, runoff and raindrop erosion of some Trinidadian soils. Biosyst. Eng. 105(1): 112-118 (7 pages).
15
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