Perceiving Complex Water Resource Systems from the Perspective of
Emergence and Information
Abstract
A challenge to managing water resources is characterizing the
scale-dependent heterogeneity created by the interactions among
hydrological, ecological and anthropological processes. It is often
difficult to collect sufficient empirical data over the range of scales
required to construct mathematical models that facilitate robust
bottom-up descriptions or predictions. An alternative is identifying
emergent properties of complex systems, whose components self-organize
into novel structures or processes via their collective interactions
with each other and the environment. A new level of organization and
complexity emerges that cannot be predicted from or attributed to the
components alone. Emergence offers a number of perspectives from which
to interpret, if not predict, the behavior of complex water resource
systems. One of these is entropy, which maximizes the options for system
components to alter their interactions and, thus, permits variability
and adaptability. At the scale of watersheds, increased entropy is
pertinent because of its relationship to information (as probability
functions), which is transmitted through connected components of a
watershed in a manner such that the accrued information gives rise to
emergent properties. Hence, analyzing the behaviors of a system
according to emergence introduces the possibility of evaluating the
information content via its interconnected components. Connectivity then
assumes an integral role in a hydrologic system’s response to natural or
anthropogenic disturbances (e.g., climate change, land use). Replacing
the details of multi-scale heterogeneity and causal mechanisms with the
functions that watersheds perform allows processes such as stream flow
rate/duration and flood frequency to be construed as emergent
spatiotemporal patterns. A reductionist or bottom-up approach to
assessing the behavior of aquatic systems shifts to a functional or
top-down approach that does not depend upon an understanding of all the
physical, chemical or biological mechanisms involved. This latter
approach could supplement conventional water resource descriptions and
predictions via more comprehensively characterizing watershed or aquatic
ecosystem functions.