Adam Weinberg
UEP 232
9/13/2012
Assignment 1: Project Topic
Residents of Sharon, Massachusetts, have documented habitat distress in the lower reaches of
Beaver Brook, a tributary of the Neponset River, approximately 18 miles south-southwest of
Boston. It has been proposed by a local watershed advocacy group that groundwater pumping by
a municipal supply well is withdrawing water from Beaver Brook, located approximately 250 ft.
from the well. This withdrawal may be responsible for degradation of the health of the Beaver
Brook ecosystem to detrimental effect upon a variety of aquatic species, including a population
of brook trout. To study the flow impacts on Beaver Brook stream flow, stream-gauges were
installed upstream and downstream of the municipal well and volunteers have collected streamflow data since 2007.
A typical watershed exhibits increased stream-flow further downstream, as the contributing
source area for the stream increases. Data collected from the stream-gauges indicates that, during
the summer months, Beaver Brook exhibits the opposite behavior. Activists suggest this is
evidence that municipal groundwater pumping is depleting stream-flow from Beaver Brook.
The questions I hope to address in this project are:
1) Are there any points between the two stream-gauges where surface-water is being
naturally diverted and unaccounted for? Local knowledge suggests that there are no
diversions between the gauges that would impact the stream, but I have no current
method to confirm this.
2) Does the spatial data provide any explanations for why Beaver Brook is losing water
besides groundwater pumping? It may be possible that the surficial geology is such that
the stream will naturally infiltrate into the aquifer in the lower reaches of the stream when
groundwater levels are lowered by increased evaporation and plant transpiration during
the summer.
Base maps that will be necessary or otherwise informative include topography, geology, and
land-use maps. Geology and topography are public domain data available through the United
States Geological Survey (USGS). Land-use maps are available through the MA Department of
Fish and Game (MA FWE). Other data required for this project is also publically available
information. Stream-gauge and rain-gauge data were obtained from the MA FWE River Instream
Flow Stewards (RIFLS) website. Groundwater pumping data was obtained from the Town of
Sharon Department of Public Works (DPW). The location of stream-gauges is noted on maps
and GPS coordinates also provided by municipal features including pumping and monitoring
wells were obtained from the DPW.
Sources
1. Garbrecht, J., Ogden, F., DeBarry, P., and Maidment, D. (2001). GIS and Distributed
Watershed Models. I: Data Coverages and Sources. Journal of Hydrological
Engineering, 6(6), 506–514.
The first of a two paper series about GIS and Distributed Watershed Models identifies “types and
sources of spatial data … illustrates GIS capabilities, and addresses GIS-model integration and
implementation issues” related to hydrological applications of GIS. There is a great introduction
to raster and vector data, map projections, and how this can be applied to stream and drainage
data. Much of the digitized stream data and other hydrographic data is available through USGS
or USEPA. Local scale soils data is available through the Soil Survey Geographic (SSURGO)
database.
2. Gerstner, C., Vogel, R. (2008). Paving Paradise: Watershed Imperviousness and Peak
Streamflow. [PowerPoint slides]. Tufts University Dissertation, retrieved from
scholarworks.umass.edu via Google Scholar.
This Tufts thesis combined GIS with hydro-statistical analysis. One of the aspects of greatest
interest to me is that Gerstner used several methods to infer permeability of land surface. There
were direct methods using MassGIS Imperviousness and National Land Cover Datasets.
However, she also inferred permeability using other datasets such as land cover and population
density, and by applying equations or coefficients to these datasets. Therefore, even if a
particular dataset of interest does not exist, it may be possible to infer data from other sources by
applying scientifically rigorous methods to evaluate the data.
3. Jones, K.L., Poole, G.C., O’Daniel, S.J., Mertes, L.A.K., Sanford, J.A. (2008). Surface
Hydrology of Low-Relief Landscapes: Assessing Surface Water Flow Impedance Using
LIDAR-derived Digital Elevation Models. Remote Sensing of Environment 112(11):
4148-4158.
This article warns that typical Digital Elevation Models (DEMs) may not be adequate for
determining hydrological flow characteristics of low topography environments with GIS. DEMs
are useful for high-relief environments, but in basins where subtle topographic divides can have
significant impacts on local hydrology, alternative data sources may be necessary. This study
found that using light detection and ranging (LiDAR) methods, 1-meter resolution maps of flow
impendences/ topographic divides were possible. These types of maps require a different type of
flow analysis- link and node network routing. Since my proposed study area is a fairly small subbasin in south-eastern Massachusetts, it is likely that this watershed could be considered lowrelief. While I am unsure whether such LiDAR data is available for this site, this paper is a great
reminder that the resolution of the data sources I utilize will be critical.
4. Ogden, F., Garbrecht, J., DeBarry, P., and Johnson, L. (2001). GIS and Distributed
Watershed Models. II: Modules, Interfaces, and Models. Journal of Hydrological
Engineering 6(6), 515–523.
The second paper is the GIS and Distributed Watershed Models series discusses applications that
are available to model hydrological characteristics of a watershed basin using GIS. Many of
these applications seem to be designed as modules to be used with GIS programs such as
ArcGIS. GRID, a component of ArcGIS, is potentially the most applicable module discussed in
the paper. GRID allows flow direction to be determined from a raster-based elevation dataset.
Flow accumulation can calculate the upstream drainage area at any particular point, and a
watershed function delineates that upstream area. I will attempt to access and use the GRID
module or some equivalent in my project as the flow direction, flow accumulation, and
watershed functions would all be very helpful.
5. Pickering, N., Rowe, G., Clarkeson, J., Jacqz, C. (2008). Using Water Budgets to Assess
Impacts on Streamflow. [PowerPoint slides]. Retrieved from scholarworks.umass.edu via
Google Scholar.
This source is a power-point presentation jointly prepared by the Charles River Watershed
Association, the MA Executive Office of Energy and Environment, MassGIS, and the
environmental consulting firm ESS Group. The presentation proposes that water budgets allow
assessment of human impacts on streamflow. The water budgets are evaluated to the sub-basin
scale on monthly time-steps. The hydrology is evaluated for stream base-flow, urban impacts to
streamflow, and impacts of utilities according to absolute impact (gallons, cfs) and relative
impact (% of natural flow). The calculations were performed using the ArcGIS Visual Basic
Tool. Water budget inputs and outputs are summarized and methodologies for data inputs
explained. Well withdrawals were converted to stream depletion using a USGS tool called
StrmDepl, which I also will be using for my thesis. This presentation confirms that my plan to
evaluate the Beaver Brook water budget using GIS is possible, and potentially is a powerful tool.
6. Rosenthal, W.D., Rrinivasan, R., Arnold, J.G. (1995). Alternative River Management
Using a Linked GIS-Hydrology Model. Trans. ASAE 47(4): 1039-1049.
This paper utilizes a GIS-hydrological model link to predict streamflow. This highly complex
hydrological simulation uses daily time-step data within a GIS framework. The layers utilized
include a digital elevation model (DEM) topographic map, soils data from STATSGO, and land
use and land cover data from USGS. Daily precipitation and temperature data from the National
Weather Service were utilized. While the model developed in this paper is far more complex
than I can hope to use, the fact that GIS and daily time-step data was integrated has a great deal
of applicability for my project.