GIS-ROUT: A River Model for Watershed Planning

10.1068/b2624 ◽  
2000 ◽  
Vol 27 (2) ◽  
pp. 231-246 ◽  
Author(s):  
Xinhao Wang ◽  
Charlotte White-Hull ◽  
Scott Dyer ◽  
Ying Yang
Keyword(s):  
Water Quality ◽  
River Water ◽  
Spatial Data ◽  
Human Activities ◽  
Environmental Changes ◽  
Research Area ◽  
Analytical Models ◽  
Watershed Planning ◽  
Quality Model ◽  
Development Scenarios

Previous studies have shown that significant environmental changes are the result of human activities such as urbanization occurring at the spatial scale of landscapes. The challenge faced by many planners today is how to understand such relationships in order to support integrated watershed planning and management. Although many mathematical models have been developed to simulate the chemical transport process in a river, few are actually used in watershed assessment and management. Recently, incorporating analytical models into GIS platforms has emerged as a promising research area attracting planners and other resource managers. In this paper we present a GIS-based river water quality model (GIS-ROUT) to predict chemistry changes in river water as a result of sewage discharge changes in a watershed. Integration of spatial data, GIS, and analytical models in GIS-ROUT makes it possible to examine the dynamic linkages between water quality and human activities in a watershed. Furthermore, the user-friendly interface of the model allows its users to concentrate on the planning issues, such as examining the “What if…” questions related to different development scenarios. The study not only contributes to the application of GIS and water quality models in planning, but it also provides a comprehensive view of the watershed that can help government agencies and other stakeholders to make informed decisions.

scholarly journals Water Quality Modeling of Bhima River by using HEC-RAS Software

2020 ◽  
Vol 9 (3) ◽  
pp. 2886-2889
Keyword(s):  
Water Quality ◽  
River Water ◽  
Hydrodynamic Model ◽  
Algal Blooms ◽  
Agricultural Runoff ◽  
Water Quality Modeling ◽  
Water Quality Model ◽  
River Water Quality ◽  
Water Levels ◽  
Quality Model

The River has got religious importance in India. The Bhima River is beginning from Bhimashankar hill and it flows through some parts of Maharashtra and Karnataka state. The assessment of water quality for the development of the places near the bank of River is important. These is controlled by various manmade activities. The quality of river water resources is facing problems because of the continuous agricultural runoff, development and urbanization. Due to mixing of nutrients causes algal blooms, which results eutrophication. The modeling of water quality can be deliberated as useful tool for assessing river water. Bhima River is demarcated as a major and important water body located in Pandharpur, dist. Solapur, Maharashtra. As Pandharpur is having historical background and known as one of the famous Holly places in Maharashtra, this place is facing huge population fluctuation due to migrated pilgrims and rapid growth of urbanization. These two things detrimentally affect River water quality. The main objective of current study was to develop a hydrodynamic model combined with river water quality model for the Bhima River to measure and recognize the processes harmful for the River. For Bhima River a hydrodynamic model was constructed using the HEC-RAS 4.1 software combined with a river water quality model to estimate the amount, distribution and sources of algae, nitrate and temperature. The river model has standardized with the help of previous water levels near the Pandharpur region. It has standardized and calibrated for the assessed parameters by competing them with the present data. The result showed a relationship between DO and temperature range. DO level in Pandharpur and Gopalpur were observed to be fluctuating with respective temperature and during Vari season. However, wastewater discharge from Nalha in sample station 3 i.e. Goplapur shows slit changes in DO and due to this there is necessity to learn other parameters also.

scholarly journals Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series

2020 ◽  
Vol 12 (21) ◽  
pp. 3622
Author(s):  
Mengmeng Cao ◽  
Kebiao Mao ◽  
Xinyi Shen ◽  
Tongren Xu ◽  
Yibo Yan ◽  
...  
Keyword(s):  
Water Quality ◽  
Human Activities ◽  
Water Surface ◽  
Algal Bloom ◽  
Environmental Changes ◽  
Climatic Factors ◽  
Dongting Lake ◽  
Dynamic Learning ◽  
Traditional Methods

Significant water quality changes have been observed in the Dongting Lake region due to environmental changes and the strong influence of human activities. To protect and manage Dongting Lake, the long-term dynamics of the water surface and algal bloom areas were systematically analyzed and quantified for the first time based on 17 years of Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The traditional methods (index-based threshold algorithms) were optimized by a dynamic learning neural network (DL-NN) to extract and identify the water surface area and algal bloom area while reducing the extraction complexity and improving the extraction accuracy. The extraction accuracy exceeded 94.5% for the water and algal bloom areas, and the analysis showed decreases in the algal bloom and water surface areas from 2001–2017. Additionally, the variations in the water surface and algal bloom areas are greatly affected by human activities and climatic factors. The results of these analyses can help us better monitor human contamination in Dongting Lake and take measures to control the water quality during certain periods, which is crucial for future management. Moreover, the traditional methods optimized by the DL-NN used in this study can be extended to other inland lakes to assess and monitor long-term temporal and spatial variations in algal bloom areas and can also be used to acquire baseline information for future assessments of the water quality of lakes.

Identifiability analysis of the CSTR river water quality model

2006 ◽  
Vol 53 (1) ◽  
pp. 93-99 ◽  
Author(s):  
J. Chen ◽  
Y. Deng
Keyword(s):  
Water Quality ◽  
River Water ◽  
Sampling Frequency ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Identifiability Analysis ◽  
Quality Models ◽  
Observational Errors ◽  
Water Quality Models

Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.

scholarly journals Extension of the River Water Quality Model No. 1 with the fate of pesticides

2011 ◽  
Vol 14 (1) ◽  
pp. 48-64 ◽  
Author(s):  
Veerle C. J. De Schepper ◽  
Katrijn M. A. Holvoet ◽  
Lorenzo Benedetti ◽  
Piet Seuntjens ◽  
Peter A. Vanrolleghem
Keyword(s):  
Water Quality ◽  
Water Column ◽  
River Water ◽  
Bulk Water ◽  
Transport Processes ◽  
Water Quality Model ◽  
River Water Quality ◽  
Model Parameters ◽  
Quality Model ◽  
Run Off

The existing River Water Quality Model No. 1 (RWQM1) was extended with processes determining the fate of non-volatile pesticides in the water phase and sediments. The exchange of pesticides between the water column and the sediment is described by three transport processes: diffusion, sedimentation and resuspension. Burial of sediments is also included. The modified model was used to simulate the concentrations of diuron and chloridazon in the river Nil. A good agreement was found between the simulated pesticide concentrations and measured values resulting from a four-month intensive monitoring campaign. The simulation results indicate that pesticide concentrations in the bulk water are not sensitive to the selected biochemical model parameters. It seems that these concentrations are mainly determined by the imposed upstream concentrations, run-off and direct losses. The high concentrations in the bulk water were not observed in the sediment pore water due to a limited exchange between the water column and the sediment. According to a sensitivity analysis, the observed pesticide concentrations are highly sensitive to the diffusion and sorption coefficients. Therefore, model users should determine these parameters with accuracy in order to reduce the degree of uncertainty in their results.

scholarly journals Relationship of dissolved inorganic carbon (DIC) concentrations with some environmental variables in the Red River water in the period 2008 - 2015

2016 ◽  
Vol 8 (2) ◽  
pp. 102-106
Author(s):  
Thi Phuong Quynh Le ◽  
Thi Xuan Binh Phung ◽  
Thi Thuy Duong ◽  
Duc Nghia Le ◽  
Tu Cuong Ho
Keyword(s):  
River Water ◽  
Human Activities ◽  
Environmental Variables ◽  
Inorganic Carbon ◽  
Environmental Changes ◽  
Dissolved Inorganic Carbon ◽  
Red River ◽  
Natural Conditions ◽  
Survey Results ◽  
The Impact

Dissolved Inorganic Carbon (DIC) is one of the main chemical components in water and very sensitive with environmental changes. DIC content in river water closely relates with natural weathering process and human activities in the whole basin. Therefore, DIC concentration reflects the impact of natural conditions and human activities in the basin to river water quality. This paper presents the survey results of the DIC concentrations at 4 sites in the Red River system during the period from January 2008 to December 2015 and simultaneously considers the relationship between some environmental variables and the DIC concentrations in the river water. The survey results showed that the DIC concentrations in the Red River water varied from 9.1 to 29.9 mgC.L-1, averaging 19.6 mgC.L-1 during the study period. The DIC concentrations are positively correlated with pH values and some major ions concentrations in river water, such as K+, Na+, Ca2+, SO42- but negatively correlated with water temperature. These relationships also indicate that the DIC concentrations in the Red River water are influenced by natural conditions, rather than by human activities in the river basin. Cacbon vô cơ hòa tan (DIC) là thành phần hóa học cơ bản trong nước và rất nhạy cảm với những thay đổi của các yếu tố môi trường. DIC có mối liên hệ chặt chẽ với sự phong hóa tự nhiên và các hoạt động của con người trên quy mô toàn lưu vực. Do đó, DIC phản ánh mức độ tác động của các điều kiện tự nhiên và con người trong lưu vực tới chất lượng nước sông. Bài báo trình bày kết quả quan trắc hàm lượng DIC trong nước sông Hồng, đồng thời xem xét mối quan hệ giữa một số yếu tố môi trường với hàm lượng DIC trong nước sông trong giai đoạn 1/2008 – 4/2015. Kết quả cho thấy hàm lượng DIC trong nước sông Hồng dao động trong khoảng 9,1 to 29,9 mgC.L-1, trung bình đạt 19,6 mgC.L-1 trong giai đoạn tháng 1 năm 2008 – tháng 12 năm 2015. Hàm lượng DIC có mối tương quan theo tỷ lệ nghịch với nhiệt độ nước sông; đồng thời có mối tương quan tỷ lệ thuận với giá trị pH và hàm lượng một số ion như K+, Na+, Ca2+, SO42-... tại 4 vị trí quan trắc trên sông Hồng. Các mối quan hệ này thể hiện rằng hàm lượng DIC trong nước sông Hồng chịu ảnh hưởng chính của các đặc điểm tự nhiên hơn là các tác động của con người trong lưu vực.

scholarly journals Keanekaragaman Makrozoobentos sebagai Indikator Kualitas Air Sungai Cisadane, Jawa Barat – Banten (Macrozoobenthos diversity as indicator of water quality of Cisadane River)

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Ratna Siahaan
Keyword(s):  
Water Quality ◽  
River Water ◽  
Human Activities ◽  
River Water Quality ◽  
Taxa Richness ◽  
Polluted Station

AbstrakSungai Cisadane memiliki multifungsi untuk kebutuhan pertanian, rumah tangga dan industri. Namun, kegiatan manusia di Daerah Aliran Sungai/DAS Cisadane dan di Sungai Cisadane dapat mengancam fungsi dan nilai ekosistem S.Cisadane. Penelitian ini bertujuan untuk menganalisis keanakeragaman makrozoobentos sebagai indikator kualitas air S.Cisadane. Penelitian dilakukan di sembilan (9) titik di sepanjang Sungai Cisadane dari hulu hingga hilir. Sampel makrozoobentos dikoleksi dengan jala surber dan Eckman Grabb. Pada musim kemarau, kekayaan taksa makrozoobentos terendah di bagian tengah dan hilir hilir (8 taksa) dan tertinggi di hulu (20 taksa). Kualitas air sungai ditentukan berdasarkan Indeks keanekaragaman Shannon-Wiener (H’). Kualitas air S.Cisadane yaitu baik/tercemar sangat ringan di hulu (Stasiun 1), cukup baik/tercemar ringan di hulu - tengah (Stasiun 2-5), sedang/tercemar sedang tengah mendekati hilir (Stasiun 6), dan buruk/tercemar berat di hilir (Stasiun 7-9).Kata kunci: kualitas air, makrozoobentos, Sungai CisadaneAbstractCisadane River has multifunction i.e. agriculture, domestic and industry. All human activities in Cisadane Watershed and in Cisadane River could threat function and value of Cisadane River. The aim of this research was to analysis macrozoobenthos diversity as bioindicator of Cisadane River. Nine (9) stations were designed along Cisadane River from up to downstream. Samples were collected with Surber net and Eckman Grabb. The taxa richness decreased from upstream (20 taxa) to downstream (8 taxa).Based on Shannon-Wiener (H’), the water quality of Cisadane River were classified i.e. good (Station 1), quite good/slightly polluted (Station 2-5), moderate/moderately polluted (Station 6), and not good/ heavily polluted (Station 7-9).Keywords: Cisadane River, water quality, macrozoobenthos

RIVER WATER QUALITY MODEL VERIFICATION THROUGH A GIS BASED SOFTWARE

2009 ◽  
Vol 42 (11) ◽  
pp. 798-803 ◽  
Author(s):  
M.K. Yetik ◽  
M. Yüceer ◽  
R. Berber ◽  
E. Karadurmuş
Keyword(s):  
Water Quality ◽  
River Water ◽  
Water Quality Model ◽  
River Water Quality ◽  
Model Verification ◽  
Quality Model
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