Identifying Major Hydrologic Change Drivers in a Highly Managed
Transboundary Endorheic Basin: Integrating Hydro-ecological Models and
Time-Series Data Mining Techniques
Abstract
The fragile balance of endorheic lakes in highly managed semi-arid
basins with transboundary water issues has been altered by the
intertwined effects of global warming and long-term water mismanagement
to support agricultural and industrial demand. The alarming rate of
global endorheic lakes’ depletion in recent decades necessitates
formulating mitigation strategies for ecosystem restoration. However,
detecting and quantifying the relative contribution of causal factors
(climate variability and anthropogenic stressors) is challenging. This
study developed a diagnostic multivariate framework to identify major
hydrologic drivers of lake depletion in a highly managed endorheic basin
with a complex water distribution system. The framework integrates the
Soil and Water Assessment Tool (SWAT) simulations with time-series
decomposition and clustering methods to identify the major drivers of
change. This diagnostic framework was applied to the Salton Sea
Transboundary Basin (SSTB), the host of the world’s most impaired inland
lake. The results showed signs of depletion across the SSTB since late
1998 with no significant changes in climate conditions. The time-series
data mining of the SSTB water balance components indicated that
decreases in lake tributary inflows (-16.4 Mm3 yr-2) in response to
decline in Colorado River inflows, associated with state water transfer
agreements, are causing the Salton Sea to shrink, not changes in the
irrigation operation as commonly believed. The developed multivariate
detection and attribution framework is useful for identifying major
drivers of change in coupled natural-human systems.