Basin-Scale, Real-Time Salinity Management Using Telemetered Sensor Networks and Model-Based Salt Assimilative Capacity Forecasts

Basin-Scale, Real-Time Salinity Management Using Telemetered Sensor Networks and Model-Based Salt Assimilative Capacity Forecasts

Nigel W.T. Quinn (Lawrence Berkeley National Laboratory, USA), Roberta Tassey (US Bureau of Reclamation, USA) and Jun Wang (US Bureau of Reclamation, USA)
Copyright: © 2015 |Pages: 29
DOI: 10.4018/978-1-4666-7336-6.ch004
OnDemand PDF Download:
List Price: $37.50


This chapter describes a new approach to environmental decision support for salinity management in the San Joaquin Basin that focuses on Web-based data sharing using tools such as YSI Econet and continuous data quality management using an enterprise-level software tool WISKI. These tools offer real-time Web-access to sensor data as well as providing the owner full control over the way the data is visualized. The same websites use GIS to superimpose the monitoring site locations on maps of local hydrography and allow point and click access to the data collected at each environmental monitoring site. This information technology suite of software and hardware work together with a watershed simulation model WARMF-SJR to provide timely, reliable, and high quality data and forecasts of river salinity that can used by stakeholder decision makers to ensure compliance with state water quality objectives.
Chapter Preview


In the past five years there has been a revolution in the way individuals share information. Social networking software applications such as Facebook, Twitter, and YouTube continue to redefine the manner by which knowledge is acquired and shared. The US Environmental Protection Agency Office of Information Technology has suggested that the next five years will witness as significant a technical revolution in data sharing technologies as the past five have provided in the ability to search. As data sharing becomes more widespread a significant constraint to the use of the information acquired is the issue of data quality. Important decisions are often made on current or real-time data – which is why, in the past, agencies preferred to establish and maintain their own monitoring stations. However, scant attention and few resources have been devoted to sharing the data from these stations with others (Maidment, 2008; Tarboton, 2005).

The Consortium for the Advancement of Hydrologic Science (CUAHSI) has developed a Hydrologic Information System architecture in an attempt to address some of the obstacles associated with data sharing on the web (Maidment, 2008). Given the rapid increase in statutory environmental regulation during the past decade and the establishment of pollutant-load regulatory frameworks in many countries such as the TMDL (Total Maximum Daily Load) in the United States (California Environmental Protection Agency, 2002), stakeholders are being obligated to support the extensive monitoring networks needed to implement these pollutant control systems. Data sharing technologies and procedures for ensuring continuous data quality assurance are necessary for sustained and cost-effective watershed-based pollutant regulation. This paper describes a prototype data acquisition, sharing and data quality assurance project developed for salinity management within the San Joaquin Basin of California (Figure 1) that takes a first step at overcoming existing impediments. The paper provides detail on wetland salinity management since the 80,000 hectare project area to which these techniques are applied was without any form of continuous environmental monitoring as recently as eight years ago. The salinity control strategy taken to manage salt exports from these San Joaquin Basin wetlands is contrasted with the Basin salinity plan adopted for the significantly larger Murray Darling Basin in south-east Australia to contrast and compare the relative merits of each program.

Figure 1.

San Joaquin River Basin showing major primary real-time monitoring stations. The east-side of the Basin produces high quality return flows that derive from the snow pack in the Sierra Nevada mountains. The west-side of the Basin produces return flows high in salt and trace elements resulting from the combination of an imported water supply and the natural salinity of the alluvial, marine-derived soils (source: California Department of Water Resources)

Key Terms in this Chapter

Stakeholder: Agricultural, wetland and municipal water users subject to the same regulatory constraints in a given watershed or drainage basin.

Electrical Conductivity (EC): An indirect measure of dissolved ions in solution using the principal of electrical conductance measured in mmhos/cm or uS/cm. Reliable sensors can be built that can measure EC continuously whereas a direct measurement of total dissolved solids requires gravimetric analysis – a slow and costly procedure.

Water Quality Objectives: The maximum pollutant concentration measured at the compliance monitoring station. Some water bodies may have several water quality objectives established for certain seasons in each water year. For example the Vernalis salinity objective is 700 uS/cm during the summer irrigation season between April 1 to August 31 each year and 1,000 uS/cm during the non-irrigation season from September 1 to March 31.

TMDL: Total Maximum Daily Load. A methodology developed by the US Environmental Protection Agency to regulate pollutant discharges into receiving waters.

Real-Time Water Quality Management: A cooperative and coordinated set of actions based on monitoring, forecast modeling, data dissemination and sharing that maximizes pollutant export while achieving compliance with river water quality objectives.

Sensor Networks: Clusters of telemetered monitoring stations that report data continuously to a central database server. These data are typically migrated to a web server so they can be accessed in real-time by anyone with web access.

Assimilative Capacity: The total mass of a pollutant that can be safely discharged into a water body such as a river without exceeding the pollutant concentration objectives measured at the downstream compliance monitoring station in that water body.

Complete Chapter List

Search this Book: