Archive for August, 2013

Coastal flood inundation monitoring

Saturday, August 31st, 2013

Early View article:Coastal Flood Inundation Monitoring with Satellite C-band and L-band Synthetic Aperture Radar Data,” by Elijah Ramsey III, Amina Rangoonwala, and Terri Bannister.

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm- and tidal-related flooding of spatially extensive coastal marshes within the north-central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L-Band SAR (PALSAR) (L-band) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C-band) data during 2006-2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels.

Their research suggests that although both PALSAR- and ASAR-based inundation mapping performance would benefit from higher frequency collections, ASAR-based performance would have a substantially higher improvement potential. In the case of ASAR in particular, a higher collection frequency would provide more choices leading to the possibility of obtaining consistently higher-quality reference scenes leading to improved inundation mapping performance. In addition, results suggest that the application of more consistent SAR imaging parameters, such as look direction and coverage would increase SAR inundation mapping performance, primarily by increasing the consistency in look angle from scene to scene. With these strategic collection changes, SAR inundation mapping could provide an improved representation of the coastal flooding dynamism.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Streambed E. coli

Wednesday, August 28th, 2013

Early View article:Assessing the Impacts of E. coli Laden Streambed Sediment on E. coli Loads over a Range of Flows and Sediment Characteristics,” by Pramod K. Pandey and Michelle L. Soupir.

In this study, the authors demonstrated the impacts of streambed on total in-stream E. coli loads. The model was developed to calculate the total in-stream E. coli load. The inclusion of streambed sediment E. coli resulted in increased levels of E. coli. For example, when neglecting the streambed sediment E. coli concentrations, the average E. coli load was 107 (CFU/s); however, when streambed sediment E. coli concentrations were included in the model, the predictions ranged from 1010 to 1014 (CFU/s). The model predictions are verified using field data and the model skill (mskill) and NSE coefficient values were 0.78 and 0.55, respectively. Results of this study suggest that monitoring streambed sediment E. coli concentrations is required to improve the assessment of in-stream E. coli concentrations.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Hetch Hetchy fire

Tuesday, August 27th, 2013

While the possible burning of the Hetch Hetchy watershed would be a tragedy, it would not necessary have a great impact on San Francisco’s water supply. In a 2007 JAWRA paper, “REASSEMBLING HETCH HETCHY: WATER SUPPLY WITHOUT O’SHAUGHNESSY DAM,” Sarah Null and Jay Lund showed the Hetch Hetchy Reservoir no longer is critical, as other, newer reservoirs downstream would take up the slack.

Groundwater and Lake Powell

Tuesday, August 27th, 2013

Early View article:Loss Rates from Lake Powell and Their Impact on Management of the Colorado River,” by Tom Myers

Regression analyses of local inflow with gaged tributaries have improved the estimate of local inflow. Using a stochastic estimate of local inflow based on the standard error of the regression estimator and of gross evaporation based on observed variability at Lake Mead, a reservoir water balance was used to estimate that more than 14.8 billion cubic meters (Gm3) has been stored in the banks, with a 90% probability that the value is actually between 11.8 and 18.5 Gm3. Groundwater models developed by others, observed groundwater levels, and simple transmissivity calculations confirm these bank storage estimates. Assuming a constant bank storage fraction for simulations of the future may cause managers to underestimate the actual losses from the reservoir. Updated management regimes which account more accurately for bank storage and evaporation could save water that will otherwise be lost to the banks or evaporation.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Groundwater trends

Monday, August 26th, 2013

Early View article:Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables,” by Robert W. Dudley, and Glenn A. Hodgkins.

Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20-year trends was in February through March, May through August, and October through November. Forty-year trend results were mixed, whereas 50-year trends indicated increasing groundwater levels. Correlations of groundwater levels with streamflow data and the relative richness of 50- to 100-year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Estimating concentrations

Saturday, August 24th, 2013

Early View article:An Optimization Method for Estimating Constituent Mean Concentrations in Base Flow-Dominated Flow,” by Laurent Ahiablame, Bernard Engel, and Indrajeet Chaubey.

A method for characterizing base flow quantity and quality for different land uses was explored using inverse modeling with two optimization techniques (a least square method and a genetic algorithm [GA] optimization), land use information, and streamflow quantity and quality data. The proposed method has the potential to effectively estimate constituent mean concentrations for pollutant load determination in gauged and ungauged watersheds, albeit more analysis with larger and more robust datasets is desirable to further refine and validate the accuracy of the approach.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.] – See more at: