Environmental Engineering Reference
In-Depth Information
contained in this topic can provide direction in
pursuit of that task. It is the author's intent to
provide a framework within which methods for
estimating recharge can be evaluated and their
suitability for a particular study assessed. Many
factors require consideration when determining
the suitability of a method. The most important
of these is the need for consistency between the
conceptual model of recharge processes and
assumptions underlying a method. The con-
tents of this topic can assist in this determin-
ation, but formulation of a sound conceptual
model must be based on hydrologic insight on
the part of the practitioner.
Water budgets of aquifers, watersheds,
streams, soil columns, or other control vol-
umes can form a basis for a conceptual model.
Conceptual models are used to select methods,
but estimates of recharge generated by differ-
ent methods can also help refine the concep-
tual model. If estimates from various methods
differ substantially, this difference may provide
insight as to the validity of one or more assump-
tions and, in turn, may lead to a revision of
the conceptual model. Good practice calls for
application of multiple methods for estimating
recharge. Many methods can be applied using
existing data, and vast amounts of accessible
data are available. Care is required, however.
Although easy-to-access data facilitate applica-
tion of many methods, inappropriate applica-
tions can be easily overlooked. Due diligence is
required for the application of any method.
Models are useful tools for exploring
hypotheses related to conceptual models and
integrating and evaluating different kinds of
data. Many readers may be reading this topic
because they are actively involved in a ground-
water-flow modeling study and are looking for
ways to evaluate recharge values used in their
models. However, groundwater-flow models
themselves are powerful tools for estimating
recharge (
Chapter 3
). Other types of models are
also useful in recharge studies, including water-
shed models (Bauer and Mastin,
1997
; Bossong
et al
.,
2003
) and unsaturated-zone flow models
(Keese
et al
.,
2005
; Walvoord and Phillips,
2004
).
Models can provide predictions of how future
changes in climate, land use, and other fac-
tors might affect recharge patterns. Models are
also useful, in a qualitative sense, for identify-
ing locations and times that are favorable for
recharge.
Exact determination of recharge will never
be possible because of the complex nature of
recharge processes, but advances in estimation
methods will occur in terms of improved data-
collection techniques and tools that will facili-
tate access to and analysis of collected data.
Recent years have seen remarkable improve-
ments in the accuracy, durability, and record-
ing capabilities of data sensors (e.g. water-level
sensors, water-quality monitors, temperature
loggers, and distributed temperature sensing
systems). Geophysical techniques for sensing
gravity and electromagnetic waves in the sub-
surface, from land surface and from remote
platforms, will continue to develop and may
eventually evolve into powerful tools for quan-
tifying recharge rates. The potential of remote-
sensing techniques to provide direct estimates
of recharge is unknown, but information on
land use, status of vegetation, and weather can
be used in water-budget models for estimating
recharge; the information may also be useful
for refining conceptual models of recharge
processes. Remote-sensing techniques are par-
ticularly valuable in developing countries that
have minimal ground-based hydrologic data-
collection networks. New analytical techniques
for detecting dissolved gas concentrations in the
part-per-trillion range may extend the period
of use of existing tracers, such as SF
6
, and may
allow other compounds to be used as tracers.
With more and more data becoming available,
learning to properly interpret new information
and to incorporate it into recharge estimation
schemes continues to be a challenge. Improved
modeling techniques and computer programs
for analyzing time series of streamflow and
stream and groundwater levels can help address
this challenge.
