Figure IV.2-6. DSM2 results on the source water and salinity (“volumetric and constituent fingerprints) for the period November 2004 to February 2005.

Slides:



Advertisements
Similar presentations
Organic Carbon and Urban Sources - What Do We Know? Michael Zanoli Department of Water Resources, Division of Environmental Services, MWQI Program CBDA.
Advertisements

Progress in Estimating Loads at Mallard Island Nicole David Lester McKee Item #4.
CCWD: Using DSM2 Historical July20, Two Applications of the DSM2 Historical Model: Modeling Contaminant Spills and Using Salinity Fingerprints to.
S A L T M O D A computer program for the prediction of the salinity of soil moisture, ground water and drainage water, the depth of the water table, and.
INTRODUCTION Land is not only one of the most defining social, political and development issues in Southern Africa, but is the most intractable element.
GEOCHEMICAL AND STABLE ISOTOPE CHARACTERIZATION OF DRIP WATER FROM POSTOJNA CAVE, SLOVENIA Magda Mandić 1 Andrej Mihevc 2, Albrecht.
Importance of Land use management on the Flood Management in the Chi River Basin, Thailand Kittiwet Kuntiyawichai Bart Schultz Stefan Uhlenbrook F.X. Suryadi.
. Topographic map of the Refuge marsh (figure provided by Dr. E.A. Meselhe based on USGS topography data). Elevations are in feet, NGVD29.Form USGS data;
Framework for Assessing the Impact of Salinity on Productivity Amy Cheung University of New South Wales Workshop: “Policy Choices for Salinity Mitigation:
Dennis P. Lettenmaier Alan F. Hamlet JISAO Center for Science in the Earth System Climate Impacts Group and Department of Civil and Environmental Engineering.
Monitoring and Pollutant Load Estimation. Load = the mass or weight of pollutant that passes a cross-section of the river in a specific amount of time.
The Calibration Process
The Effect of Soil Hydraulic Properties and Deep Seepage Losses on Drainage Flow using DRAINMOD Debjani Deb 26 th April, 2004.
St. Johns River Water Supply Impact Study by Getachew Belaineh Ph. D., P.H. 1 Brian McGurk P.G. 1 Louis Motz Ph. D., P.E 2 Follow up Review meeting March,
Data for Irrigation Modelling Hector M Malano. Outline Modelling: what processes? What data gaps are there? Frequency of collection Level of disaggregation.
Temporal and Spatial Variability in Nitrate in Subsurface Drains in a Midwestern Agricultural Watershed Paul Capel, USGS, National Water-Quality Assessment.
Department of Agricultural and Biological Engineering
In-Delta Storage Process OverviewProcess Overview Program BenefitsProgram Benefits Project CostsProject Costs IssuesIssues Proposed Work Plan for FY 2003Proposed.
Earth Science: 15.1 Ocean Water and Life
1. Introduction The Big Darby Creek is categorized as a national scenic river with an array of biological species. Since this is one of the last pristine.
Introduction A GENERAL MODEL OF SYSTEM OPTIMIZATION.
RA-228 AND RA-226 FROFILES FROM THE NORTHERN SOUTH CHINA SEA Hsiu-Chuan Lin, Yu-Chia Chung and Chi-Ju Lin Institute of Marine Geology and Chemistry, National.
Soil management Tony Pitt. Six years of soil testing In 2005/06, recycled water use was fairly minor – just 47 farms with more than 1 ML/ha. For 2006/07,
Presenting Model Results: Synergy & Opportunities Ted Swift, Ph.D. Real-Time Data & Forecasting Project, DWR Municipal Water Quality Investigations Branch.
Water Quality Monitoring and Constituent Load Estimation in the Kings River near Berryville, Arkansas 2009 Brian E. Haggard Arkansas Water Resources Center.
1 Delta Island Agriculture Technical Workshop on Modeling Issues of the Delta February 6, 2007 Jim Wilde, P.E. Delta Modeling Section California Department.
Salinity and Bulk Water Workshop 27 October 2010 Werribee Irrigation District.
Modes of Sustainability Definition  In text  In aquifer-storage terms  In water-budget terms  In physical changes at the river (natural side)
DSM2 Performance Measures Tara Smith CWEMF Annual Meeting February 26, 2007 Delta Modeling Section Bay Delta Office.
DRAINMOD APPLICATION ABE 527 Computer Models in Environmental and Natural Resources.
Experiences in assessing deposition model uncertainty and the consequences for policy application Rognvald I Smith Centre for Ecology and Hydrology, Edinburgh.
Review of SWRCB Water Availability Analysis Emphasis on Dry Creek Water Availability Analysis.
Modeling Issues of the Delta Salinity Jamie Anderson Ph.D., P.E. CWEMF Workshop February 6, 2007 Modeling Support Branch Bay Delta Office.
Flatford Swamp Hydrologic Restoration Feasibility Study (H089)
Our Case Study. Rationale for study The TMDL model assumes that there is no decrease in seepage during low flow conditions, basing its calculations on.
Casey Andrews SOIL 4213 April 22, 2009
Changes to the 1995 Water Quality Control Plan Program of Implementation Presented by: Steve Ford Department of Water Resources.
DSM2 Analysis of Water Level and Water Quality in the South Delta Presented to California Water and Environmental Modeling Forum February 26, 2007 Fingerprinting.
Hydrology and application of the RIBASIM model SYMP: Su Yönetimi Modelleme Platformu RBE River Basin Explorer: A modeling tool for river basin planning.
Variable Load on Power Stations
Uncertainty and Reliability Analysis D Nagesh Kumar, IISc Water Resources Planning and Management: M6L2 Stochastic Optimization.
Delta Cross Channel Gates. A “gate” formulation ——— Q =  A 3 √ 2g  h Matthai,H.F Measurement of peak discharge at width contractions by indirect.
Goal of Stochastic Hydrology Develop analytical tools to systematically deal with uncertainty and spatial variability in hydrologic systems Examples of.
Overview of Discussion  What are the pros and cons of the options?  Are there other options? A2 SUBCOMMITTEE.
Ground Water Assessment Drought Management Advisory Council Meeting March 24, 2011 Nat Wilson ( or Ground Water Management.
Model Description Sample Results Next Steps Monitoring Data (Initial Conditions) Hydrodynamics Water Quality USGS; DWR Monitoring Data (Initial Conditions)
A Mass Balance Approach to Evaluate Salinity Sources in the Turlock Groundwater Sub-basin Presentation to Technical Advisory Committee, Central Valley.
2016 Water Inventory and Analysis Report Highlights on Land Use, Water Supply, and Water Budgets Christina Buck, PhD Water Resources Scientist Board of.
Activity 27 Investigating Boomtown’s Weather
CWEMF Annual Meeting March 2005
Continuous Surrogate Monitoring for Pollutant Load Estimation in Urban Water Systems Anthony A. Melcher, USU Civil and Environmental.
Delta Water Conveyance — Water Project Operations and Risks
The Calibration Process
Radar/Surface Quantitative Precipitation Estimation
José J. Hernández Ayala Department of Geography University of Florida
Nonpoint Source Pollution
Activity 27 Investigating Boomtown’s Weather
CLIMATE Key question #10 What is the difference between climate and weather? How do we pictorially represent climate over a year?
Saline Soil.
Saline Soil.
Jim McClelland Rae Mooney University of Texas at Austin
Beta Release of Delta Channel Depletion Model (DCD v1
Issue 4b - Addressing Local Degradation -
Open water area Franks Tract
Water Scarcity and Drought EEA Assessment
Red River Chloride Control Project
VERIFYING THE INCREASE OF SALINITY INTRUSION AT INTERANNUAL SCALE IN THE VIETNAM MEKONG RIVER Im going to talk about my research is verifying the increase.
Chapter Four RUNOFF When a storm occurs, a portion of rainfall infiltrates into the ground and some portion may evaporate. The rest flows as a thin sheet.
Central Valley Salinity Coalition
Systems and Components – A Process for Developing the Total Water Budget Handbook for Water Budget Development - With or Without Models CWEMF 2019 Annual.
Presentation transcript:

Figure IV.2-6. DSM2 results on the source water and salinity (“volumetric and constituent fingerprints) for the period November 2004 to February 2005. Reproduced from DWR (2005). Current DWR DPLA weekly report identifies individual sources of salt. A reasonable range of drainage salinity could be used to quantify part of the uncertainty. Ted Swift will talk more on this later on.

Modeling Issues with In-Delta Agricultural Uses Drainage salinity Drainage volume Net depletion

Figure IV.2-1. Approximate sampling locations of agricultural drainage salinity by DWR's Municipal Water Quality Investigation Program, data collected between 1986 and 1997. Data available at http://wdl.water.ca.gov/wq-gst/

Figure IV.2-2. Agricultural drainage salinity in south and southeast Delta. Drainage salinity at different pump stations on the same island (e.g. Kings Island) could be significantly different. Same symbol is used for different drainage pumps on the same island. Is it the island or is it the source water? Kings Island is low because of ESS? What about Empire Tract also on the east side? It’s all over the map. SJR water on one side and ESS on the other? Pescadero is high because of SJR? Woodward and Bacon are low because of the “through-Delta” flow from Sacramento?

Figure IV.2-5. Model input and recent measurements of agricultural drainage salinity in the Delta. Caveat: Not meant to be representative. This comparison is driven entirely by the data available.

Observations Wide scatter of drainage salinity: between islands between years between months Model input could be significantly different from field measurements Source tracking could be a solution Wide scatter of drainage salinity: from island to island (and even on same island) from year to year (Is hydrology a key factor?) from month to month Model input could be significantly different from field measurements. With the large number of drainage pumps in the Delta, each with uncertain volume of discharge, it would be impossible to obtain a reliable estimate. Would tracking the salt load from Delta islands be a feasible approach?

Issues Drainage salinity Drainage volume Net depletion Uncertainty between two studies 40 years apart.

1954, 1955 estimates made by DWR; 1995, 1996 by USGS; both estimates are based on power use and pump test data. Part of the difference between years may be due to difference in rainfall. Differences in drainage volumes in the summer, however, could be indicative of different crop types, irrigation pattern, or uncertainty in estimates. WY Sac SJR 1954 – AN BN 1955 – D D 1995 – W W 1996 – W W Jung, M. And Q. Tran. 1998. Delta island drainage volume estimates, 1954-1955 versus 1995-1996. Report to DWR, MWQI Program.

Jung, M. And Q. Tran. 1998. Delta island drainage volume estimates, 1954-1955 versus 1995-1996. Report to DWR, MWQI Program. Location definition for following graph

Factors: rain, need for leaching, seepage, amount of applied water and crop types Considerable difference. Is it the methodology? Or is it intrinsic variation? Or both? Is it a realistic goal to strive for “a” number? Jung, M. And Q. Tran. 1998. Delta island drainage volume estimates, 1954-1955 versus 1995-1996. Report to DWR, MWQI Program.

Issues Drainage salinity Drainage volume Net depletion An overview of the magnitude of the implication.

Huge difference in Rock Slough chloride concentration for a difference of 500 cfs at steady state.

Observations Drainage salinity Highly variable (season, island, year) Higher salinity assumed in model Drainage volume Large difference in 2 field estimates Net depletion Uncertainty of even a few hundred cfs could lead to large difference in simulated salinity