Textural patches (i.e., grain-size facies) are commonly observed in gravel-
bed channels and are of significance for both physical and biological proce
sses at subreach scales. We present a general framework for classifying tex
tural patches that allows modification for particular study goals, while ma
intaining a basic degree of standardization. Textures are classified using
a two-tier system of ternary diagrams that identifies the relative abundanc
e of major size classes and subcategories of the dominant size. An iterativ
e procedure of visual identification and quantitative grain-size measuremen
t is used. A field test of our classification indicates that it affords rea
sonable statistical discrimination of median grain size and variance of bed
-surface textures. We also explore the compromise between classification si
mplicity and accuracy. We find that statistically meaningful textural discr
imination requires use of both tiers of our classification. Furthermore, we
find that simplified variants of the two-tier scheme are less accurate but
may be more practical for field studies which do not require a high level
of textural discrimination or detailed description of grain-size distributi
ons. Facies maps provide a natural template for stratifying other physical
and biological measurements and produce a retrievable and versatile databas
e that can be used as a component of channel monitoring efforts.