Environmental Engineering Reference
In-Depth Information
are analyzed; examples of model applications
are also presented. Model calibration and use
of inverse modeling techniques, topics that
apply to all models, are described in
Section 3.2
.
Section 3.7
describes modeling tools for upscal-
ing point estimates of recharge to obtain inte-
grated estimates at the watershed or regional
scale. Aquifer vulnerability to contamination
is addressed in
Section 3.8
because estimates
of recharge used in vulnerability assessments
are often generated by one of the modeling
approaches described in the preceding sections;
the link between model recharge estimates
and aquifer vulnerability studies is discussed.
Proper model application and interpretation
of results require a sound understanding of
assumptions inherent to that particular model.
It is not possible to include in this chapter all
the details of every model discussed. Readers
considering application of a model are directed
to cited references for exact model details.
1° by 2° topographic quadrangle units and are
distributed by state or territory.
The Natural Resources Conservation Service
has digitized soil maps for most of the United
States and compiled that information into
the Soil Survey Geographic (SSURGO) dataset
(http://soils.usda.gov/survey/geography/ssurgo/
description.html; accessed September 22, 2009).
SSURGO data are available at much finer spatial
resolution (scales of 1:12 000 to 1:63 360) than
STATSGO2 data. In addition to soil descrip-
tions, information such as available water cap-
acity and land-use category are included in the
SSURGO dataset.
Elevation data for the United States are avail-
able from the US Geological Survey (USGS). The
National Elevation Dataset (NED) is a seamless
digital raster product derived primarily from
USGS 30 m digital elevation models (DEMs)
along with higher resolutions where available
(http://eros.usgs.gov/; accessed December 15,
2009). Global elevation data are also available
from the USGS at a horizontal grid spacing
of approximately 1 km (http://eros.usgs.gov/;
accessed December 15, 2009).
The National Land Cover Data 1992 (NLCD
92) is a 21-category land-cover classifica-
tion scheme that has been applied over the
United States. It is primarily based on Landsat
Thematic Mapper images from 1992 (http://
eros.usgs.gov/; accessed December 15, 2009). In
addition to the land-cover classification, data
on topography, census, agricultural statistics,
and soil characteristics are also available. The
classification is provided as raster data at a
spatial resolution of 30 m. The classification
is currently (2010) being revised on the basis
of 2001 imagery by the Multi-Resolution Land
Characteristics (MRLC) consortium (http://
eros.usgs.gov/; accessed December 15, 2009).
The USGS also provides global land-cover char-
acterization at a 1-km scale (http://eros.usgs.
gov/; accessed December 15, 2009). The charac-
terization is based on imagery from 1992 and
1993 from the Advanced Very High Resolution
Radiometer (AVHRR); ancillary data include
digital elevation data, ecoregions interpreta-
tion, and vegetation and land-cover maps.
3.1.1 Data sources
Table 2.1
provides a list of sources for real-time
and historical hydrologic data. Data obtained
from those sources can be used as input for many
of the models discussed herein. Additional data
on soil properties, land-surface elevation, land
cover, and other features may be required for
some models, such as watershed and soil-water-
budget models; these data are also useful in
upscaling procedures, for example, in develop-
ment of regression equations to relate recharge
estimates to climate, land use, and soils. Sources
for these additional data are briefly described in
this section.
The US General Soil Map (STATSGO2) is a
digital dataset of soil information for the United
States. The 2006 release of STATSGO2 supersedes
the State Soil Geographic (STATSGO) dataset
published in 1994. The dataset was developed by
the National Cooperative Soil Survey and is dis-
tributed by the Natural Resources Conservation
Service (http://soils.usda.gov/survey/geography/
statsgo/description.html; accessed September
22, 2009). The dataset consists of georefer-
enced digital data on physical and chemical
properties of soils. The data were collected in
