scholarly journals Water quality management using statistical analysis and time-series prediction model

2014 ◽  
Vol 4 (4) ◽  
pp. 425-434 ◽  
Author(s):  
Kulwinder Singh Parmar ◽  
Rashmi Bhardwaj
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Statistical Analysis ◽  
Quality Management ◽  
Prediction Model ◽  
Time Series Prediction ◽  
Water Quality Management

scholarly journals River Dissolved Oxygen Prediction Based on Random Forest and LSTM

2021 ◽  
Vol 37 (5) ◽  
pp. 901-910
Author(s):  
Juan Huan ◽  
Bo Chen ◽  
Xian Gen Xu ◽  
Hui Li ◽  
Ming Bao Li ◽  
...  
Keyword(s):  
Water Quality ◽  
Random Forest ◽  
Quality Management ◽  
Dissolved Oxygen ◽  
Prediction Model ◽  
Water Quality Management ◽  
Quality Data ◽  
Mean Square ◽  
Water Quality Data ◽  
Better Than

HighlightsRandom Forest (RF) and LSTM were developed for river DO prediction.PH is the most important feature affecting DO prediction.The model base on RF is better than the model not on RF, and the dimensionality of the input data is reduced by RF.RF-LSTM model is outperformed SVR, RF-SVR, BP, RF-BP, LSTM, RNN models in DO prediction.Abstract. In order to improve the prediction accuracy of dissolved oxygen in rivers, a dissolved oxygen prediction model based on Random Forest (RF) and Long Short Term Memory networks (LSTM) is proposed. First, the Random Forest performs feature selection, which reduces the input dimension of the data and eliminates the influence of irrelevant variables on the prediction of dissolved oxygen. Then build the LSTM river dissolved oxygen prediction model to fit the relationship between water quality data and dissolved oxygen, and finally use real water quality data in the river for verification. The experimental results show that the mean square error (MSE), absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and coefficient of determination (R2) of the RF-LSTM model are 0.658, 0.528, 13.502, 0.811, 0.744, respectively, which are better than other models. The RF-LSTM model has good predictive performance and can provide a reference for river water quality management. Keywords: Dissolved oxygen prediction, LSTM, Random forest, Time series, Water quality management.

Water Quality Management – A Total Catchment Management Approach

1989 ◽  
Vol 21 (2) ◽  
pp. 281-288 ◽  
Author(s):  
W. J. Hawkins ◽  
D. A. Geering
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Water Quality Management ◽  
Management Approach ◽  
Catchment Management ◽  
Know How ◽  
Wild And Scenic Rivers ◽  
Resource Managers ◽  
Resource Protection ◽  
Development Resource

Water quality standards set in the past have not helped resource managers in the decisions that they face in seeking sustainable development. Resource managers are looking for meaningful information on water quality so as to evaluate the resource, set priorities for action, and to monitor progress. Resource managers need to know how water quality affects, and is affected by, catchment uses and activities. Examples of three wild and scenic rivers, the Nymboida, Murrumbidgee, and Hawkesbury/Nepean River systems, demonstrate how a ‘Total Catchment Management' approach to resource use and resource protection has advantages for water quality management.

The Gulf Coast Waste Disposal Authority: A Regional Approach to Water Quality Management

1984 ◽  
Vol 16 (5-7) ◽  
pp. 473-480
Author(s):  
L Jack Davis
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Waste Disposal ◽  
Gulf Coast ◽  
Water Quality Management ◽  
Public And Private ◽  
Public Agency ◽  
Public Managers ◽  
Public Reaction ◽  
Public And Private Sector

The Gulf Coast Waste Disposal Authority is a regional public agency created by the State of Texas to design and implement water quality management systems in three counties surrounding Galveston Bay. This article will outline the water quality management strategy employed by the Authority for a highly industrialized and populated region. Regional treatment and public and private sector cooperation will be presented as a management objective for muncipal and industrial waste disposal. A description of the background and operations of the Authority will be included along with examples of joint or combined wastewater treatment. The pressing problem of hazardous waste management in Texas will be discussed. The Authority's experiences with facility siting and public reaction will be summarized and a new approach to help resolve these issues will be presented. The article will conclude with some thoughts on strategic planning for public managers.

Sign in / Sign up

Export Citation Format

Share Document