Development of Agricultural Watershed Management System for Hydrologic and Water Quality Data Management and Analysis

2006 ◽  
Author(s):  
Hak Kwan Kim ◽  
Seung Woo Park ◽  
Sang Min Kim
Keyword(s):  
Water Quality ◽  
Data Management ◽  
Watershed Management ◽  
Management System ◽  
Agricultural Watershed ◽  
Quality Data ◽  
Water Quality Data

Implementation of a large scale water quality data management system

1976 ◽  
Vol 10 (1) ◽  
pp. 31-36 ◽  
Author(s):  
William D. Haseman ◽  
Clyde Holsapple ◽  
Andrew B. Whinston
Keyword(s):  
Water Quality ◽  
Data Management ◽  
Management System ◽  
Large Scale ◽  
Data Management System ◽  
Quality Data ◽  
Water Quality Data

Water quality monitoring: the basis for watershed management in the Oldman River Basin, Canada

2006 ◽  
Vol 53 (10) ◽  
pp. 153-161 ◽  
Author(s):  
C.W. Koning ◽  
K.A. Saffran ◽  
J.L. Little ◽  
L. Fent
Keyword(s):  
Water Quality ◽  
Point Source ◽  
River Basin ◽  
Watershed Management ◽  
Health Concern ◽  
Quality Data ◽  
Oil And Gas Development ◽  
Water Quality Data ◽  
Oldman River Basin ◽  
Oldman River

The Oldman River flows 440 km from its headwaters in south-western Alberta, through mountains, foothills and plains into the South Saskatchewan River. Peak flows occur in May and June. Three major reservoirs, together with more than a dozen other structures, supply water to nine irrigation districts and other water users in the Oldman basin. Human activity in the basin includes forestry, recreation, oil and gas development, and agriculture, including a large number of confined livestock feeding operations. Based on the perception of basin residents that water quality was declining and of human health concern, the Oldman River Basin Water Quality Initiative was formed in 1997 to address the concerns. There was limited factual information, and at the time there was a desire for finger pointing. Results (1998–2002) show that mainstem water quality remains good whereas tributary water quality is more of a challenge. Key variables of concern are nutrients, bacteria and pesticides. Point source discharges are better understood and better regulated, whereas non-point source runoff requires more attention. Recent data on Cryptosporidium and Giardia species are providing benefit for focusing watershed management activities. The water quality data collected is providing a foundation to implement community-supported urban and rural better management practices to improve water quality.

scholarly journals A new online monitoring and management system for accidental pollution events developed for the regional water basin in Ningbo, China

2011 ◽  
Vol 64 (9) ◽  
pp. 1828-1834 ◽  
Author(s):  
Gaosheng Zhang ◽  
Linlin Chen ◽  
Yuedan Liu ◽  
TaeSoo Chon ◽  
Zongming Ren ◽  
...  
Keyword(s):  
Water Quality ◽  
Management System ◽  
Online Monitoring ◽  
Water Quality Management ◽  
Warning System ◽  
Quality Data ◽  
Self Organizing Map ◽  
Water Quality Data ◽  
Accidental Pollution ◽  
Pollution Events

Due to urgency of the accidental pollution events (APE) on one side and the variability in water quality data on the other side, a new online monitoring and management system (OMMS) was developed for the purpose of sustainable water quality management and human health protection as well. The Biological Early Warning System (BEWS) based on the behavioral responses (behavior strength) of medaka (Oryzias latipes) were built in combination with the physico-chemical factor monitoring system (PFMS) in OMMS. OMMS included a monitoring center and six monitoring stations. Communication between the center and the peripheral stations was conducted by the General Packet Radio Service (GPRS) network transmission complemented by a dial-up connection for use when GPRS was unavailable. OMMS could monitor water quality continuously for at least 30 days. Once APEs occurred, OMMS would promptly notify the administrator to make some follow up decisions based on the Emergency Treatment of APE. Meanwhile, complex behavioral data were analyzed by Self-Organizing Map to properly classify behavior response data before and after contamination. By utilizing BEWS, PFMS and the modern data transmission in combination, OMMS was efficient in monitoring the water quality more realistically.

WaterScope: an innovative water quality information management system

2004 ◽  
Vol 4 (5-6) ◽  
pp. 409-414
Author(s):  
J.R. Howard ◽  
J. Lucas ◽  
J. Maitland ◽  
P. Tarrant ◽  
T. Watson
Keyword(s):  
Water Quality ◽  
Management System ◽  
Information Management System ◽  
Geographical Information ◽  
Direct Access ◽  
Quality Data ◽  
Incident Management ◽  
Quality Information ◽  
Management Support ◽  
Water Quality Data

SA Water is a State owned organisation that owns and manages South Australia's water supplies, providing reliable drinking water to nearly 1.4 million South Australians. A major issue affecting SA Water's ability to manage water quality effectively has been the difficulty accessing water quality information which has been stored in separate, generally inaccessible databases with poor reporting and decision support capability. To improve SA Water's ability to make timely and effective decisions regarding water quality, an integrated business system has been developed which provides water managers with direct access to comprehensive water quality information. The system includes improved field data collection units which incorporate a barcode system; sample point images and workflow support tools; an integrated water quality data warehouse with automated standard and ad hoc reporting capabilities; a geographical information system containing comprehensive coverages of natural resources and system infrastructure information; and water incident exception reporting and incident management support through a corporate incident management system. Major benefits of the system will include improved management of public health risk through quicker and more accurate reporting of incidents; improved customer confidence in SA Water; improved knowledge capture and visibility of water quality information; increased efficiency of capital utilisation and better understanding of system performance through spatial representation of data and trending of results. WaterScope can also be used and shared by data partners and regulators, making optimal use of the State's limited water quality data sets. It can also be made available commercially to other water management organisations. Future challenges include the integration of wastewater and recycled water data, linking of continuous (on-line) water quality data and links to water demand management systems.

Stochastic structures between quantity and quality responses of rainfall-runoff at an upland agricultural watershed

2001 ◽  
Vol 44 (7) ◽  
pp. 91-104 ◽  
Author(s):  
S. H. Kim ◽  
J. W. Delleur
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Stochastic Structure ◽  
Agricultural Watershed ◽  
Quality Data ◽  
Water Quality Parameter ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Water Quality Data ◽  
Transport Pathways

The causality between hydrologic parameters and water quality variations has been studied for a small upland agricultural watershed using a time-series analysis approach. The stage at the outlet of the watershed, which is a proxy for the outflow, and the average saturation deficit, which is a surrogate for the groundwater level, were used as hydrologic variables. The stages were measured at a triangular weir at the watershed outlet. The saturation deficits were obtained by means of a rainfall-runoff simulation model for agricultural upland watersheds (an extended version of TOPMODEL). Sequential water quality data were also collected at the watershed outlet. A systematic procedure for testing the causality between the hydrologic and water quality time-series is presented and used to investigate possible relationships between the two systems. The stochastic structure of a causality between hydrologic and water quality systems is shown. This stochastic structure is associated not only with the transport pathways (surface or subsurface) of each water quality parameter but also with the characteristics of the rainfall events.

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