Hydrological and Environmental Modeling Analyses of Pervious Pavement Impact in a Coastal City

Author(s):  
Shiguo Xu ◽  
Jihui Gao
Author(s):  
Markus T Lasut ◽  
Adianse Tarigan

A study on water quality status of three riverine systems, S. Bailang (SB), S. Maasing (SM), and S. Tondano (ST), in coastal city of Manado, North Sulawesi Province, has been conducted to measure several water quality parameters, to analyse source and quality of wastewater discharge, and to assess the status of the rivers related to the water quality. Measurement of the parameters was conducted using three indicators, i.e. organic (BOD5) and in-organic (N-NO3 and P-PO4), and pathogenic microorganism (Escherichia coli [EC] and total coliform [TC]). The result showed that the level of water quality varied between the rivers. The average level of water quality (based on the observed parameters) in SB, respectively, was 0.317 mg/l, 0.093 mg/l, 2 mg/l, >2420 MPN, and  >2420 MPN; in SM, respectively, was 0.029 mg/l, 1.859 mg/l, 17.7 mg/l, >2420 MPN, and >2420 MPN; and in ST, respectively, was 0.299 mg/l, 0.252 mg/l, 3.5 mg/l, >2420 MPN, and >2420 MPN. The level of water quality between the rivers was not significantly different (p>0.05), except based on the parameter of N-NO3 which was significantly different (p<0.01). The status of the observed rivers varied based on the classes of their water utilities (according to the Government Regulation of Indonesia, No. 82, 2001); mostly was "unsuitable". Kajian tentang status kualitas air di 3 perairan sungai di kota pesisir Manado, S. Bailang (SB), S. Maasing (SM), dan S. Tondano (ST), Provinsi Sulawesi Utara, telah dilakukan yang bertujuan untuk mengukur beberapa parameter kualitas air, menganalisis sumber dan kualitas buangan limbah domestik, dan menilai status ketiga perairan sungai tersebut. Tiga indikator digunakan, yaitu: bahan organik (BOD5), bahan anorganik (N-NO3 dan P-PO4), dan mikroorganisme patogenik (Escherichia coli [EC] dan coliform total [TC]). Hasil kajian menunjukkan bahwa tingkat kualitas air perairan tersebut berbeda-beda. Konsentrasi rerata parameter kualitas air  (BOD5, N-NO3, P-PO4, EC, dan TC) di SB, berturut-turut, sebesar 0.317 mg/l, 0.093 mg/l, 2 mg/l, >2420 MPN, dan >2420 MPN; di SM, berturut-turut, sebesar 0.029 mg/l, 1.859 mg/l, 17.7 mg/l, >2420 MPN, dan >2420 MPN; dan di ST, berturut-turut, sebesar 0.299 mg/l, 0.252 mg/l, 3.5 mg/l, >2420 MPN, dan >2420 MPN. Konsentrasi kualitas air ketiga sungai tersebut tidak berbeda secara signifikan (p>0.05), kecuali parameter N-NO3 (p<0.01). Secara umum, kondisi kualitas air ketiga sungai tersebut, menurut Peraturan Pemerintah No. 82, 2001) berada dalam status “tidak cocok” untuk peruntukannya.


2014 ◽  
Vol 31 (3) ◽  
pp. 273 ◽  
Author(s):  
Yongpeng Tong ◽  
Xin Hao ◽  
Huibin Sun ◽  
Jinxing Feng ◽  
Xiaohong Liu ◽  
...  
Keyword(s):  

2015 ◽  
Vol 48 (5) ◽  
pp. 321-330
Author(s):  
Mi Eun Kim ◽  
◽  
Young Su Jang ◽  
Chil Ho Nam ◽  
Hyun Suk Shin

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1045-1056 ◽  
Author(s):  
Thomas O. Barnwell ◽  
Linfield C. Brown ◽  
Wiktor Marek

Computerized modeling is becoming an integral part of decision making in water pollution control. Expert systems is an innovative methodology that can assist in building, using, and interpreting the output of these models. This paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes elements of an expert advisor for the stream water quality model QUAL2E. Some general conclusions are presented about the tools available to develop this system, the level of available technology in knowledge-based engineering, and the value of approaching problems from a knowledge engineering perspective.


2021 ◽  
Vol 13 (10) ◽  
pp. 5503
Author(s):  
Roghayeh Sadeghi Pasvisheh ◽  
Marie Anne Eurie Forio ◽  
Long Tuan Ho ◽  
Peter L. M. Goethals

As an “international aquatic ecosystem” in Northern Iran, the Anzali wetland is a nursery for fish and a breeding and wintering area for a wide variety of waterfowl. The wetland is threatened by human activities (deforestation, hunting, tourism, and urbanization), leading to habitat destruction, eutrophication, and sediment accumulation. To stop the degradation and to set up effective protection and restoration in line with the Sustainable Development Goals, scientific insights must be integrated into a practical framework for evidence-based support for policymakers and managers of the Anzali wetland. In this study, the Drivers–Pressure–State–Impact–Response (DPSIR) framework is used as a suitable tool to link human pressures and state changes to derive an overview of the potential impacts. Population growth, intensive agriculture, increased urbanization, and industrialization are the major driving forces that have led to a complex cascade of state changes. For instance, during recent years, water quality deterioration, habitat degradation, and the overgrowth of invasive species in the Anzali wetland watershed have caused negative socio-economic and human health impacts. Integrated and innovative monitoring programs combined with socio-environmental modeling techniques are needed for a more evidence-based management approach as part of a multiresponse strategy for the sustainable development of the wetland system. In this respect, there is a critical gap in useful information concerning biological composition and innovative monitoring methods. Moreover, the relation of biota with human activity and environmental conditions needs to be better quantified. Therefore, ecological modeling techniques based on machine learning and statistics were reviewed for their advantages and disadvantages. The overview of approaches presented here can serve as the basis for scientists, practitioners, and decision-makers to develop and implement evidence-based management programs for the Anzali wetland.


Sign in / Sign up

Export Citation Format

Share Document