1934RE: [ai-geostats] Kriging along streams
- Feb 24, 2005Edzer,
You are right about river networks.
I do think that the uni-directionality of flow is not necessarily a problem
in terms of what can inform what. Statistically, a downstream station can
inform an upstream station because what is downstream is there because of
what happened upstream, and the same for past and future. While there may
not be a *physical* link from future to past, there will still be a
*statistical* link from future to past as long as there was a statistical
link from past to future. [That is the idea in inverse modeling for example
(which are a combination of physical and statistical modeling)].
Intuitively, kriging backwards might have to be done according to a
different model than forward, but, I am open to surprises. It is worth a
From: Edzer J. Pebesma [mailto:e.pebesma@...]
Sent: Thursday, February 24, 2005 5:19 PM
To: Noemi Barabas
Cc: oscar garcia; ai-geostats@...
Subject: Re: [ai-geostats] Kriging along streams
Noemi, the idea of transforming to a one-dimensional situation,
distance along river, was the first one I got. Then, I rejected
it because it will not work for river networks; it will for a
single sections without joints though. Space-time modelling may
be complicated by the fact that there will be a strong
correlation with future observations downstream, but not with
observations upstream because water flows down; this may call
for another translation of space-time using flow speed to get
to a space-time coordinate system where the usual models make
Noemi Barabas wrote:
> Dear Oscar,what
> It sounds like you need kriging in a single dimension. If so, I think
> you need to do is a kind of coordinate transformation, for example usingto
> river mile as your distance vector. You would also need to pay attention
> the dates of the samples. Variation in time might obscure spatial trendsdifferent
> along the river's course if you just have a few sampling events at
> times for the stations.differ
> If you have data in space as well as time, there are several methods for
> space-time interpolation. Constructing correlograms for data vs time on
> paired stations could give you an idea of what constitutes a data pair for
> kriging purposes in terms of the time lag between them. Methods will
> depending on whether it is the time or space dimension that is moredensely
> References on techniques include the following:
> For straightening rivers (which might be more involved than you need):
> Barabas, N., Goovaerts, P. and P. Adriaens. 2001. Geostatistical
> and validation of uncertainty for three-dimensional dioxin data from35(16):
> sediments in an estuarine river. Environmental Science & Technology,
> For space-time data:
> Pebesma and de Kwaadsteniet (1997) Mapping spatial and temporal variation
> groundwater quality in the Netherlands. In GeoENVI - Geostatistics forthe body (plain text format) of an email message to sympa@...
> Environmental Applications, eds., Soares et al, pp. 139-151. Kluwer
> Academic Publishers, Netherlands.
> Kyriakidis and Journel (1999) Geostatistical space-time models: A review.
> Mathematical Geology (not sure which volume etc.)
> Heuvelink et al (1996) Spatio-temporal kriging of soil water content. In
> Geostatistics Wollongong '96, eds Baafi and Schofield. pp. 1020-1030.
> Kluwer Academic Publishers,Netherlands.
> -----Original Message-----
> From: oscar garcia [mailto:osgarcia@...]
> Sent: Thursday, February 24, 2005 11:56 AM
> To: ai-geostats@...
> Subject: [ai-geostats] Kriging along streams
> Dear list members,
> I want to perform kriging of water quality indicators
> measured in stations along a river course, so Can you
> help me with references about kriging along streams in
> a river basin?? is there software to perform this kind
> of analysis???
> Thanks in advance for your help,
> Oscar Javier García-Cabrejo
> Master in Hydrosystems, Civil Engineering Department
> Pontificia Universidad Javeriana
> Bogota, Colombia
> South America
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