Abstract. The complexity and heterogeneity of human water use over large
spatial areas and decadal timescales can impede the understanding of
hydrological change, particularly in regions with sparse monitoring of the
water cycle. In the Arkavathy watershed in southern India, surface water
inflows to major reservoirs decreased over a 40-year period during which
urbanization, groundwater depletion, modification of the river network, and
changes in agricultural practices also occurred. These multiple, interacting
drivers combined with limited hydrological monitoring make attribution of the
causes of diminishing water resources in the watershed challenging and impede
effective policy responses. To mitigate these challenges, we developed a novel,
spatially distributed dataset to understand hydrological change by
characterizing the residual trends in surface water extent that remain after
controlling for precipitation variations and comparing the trends with
historical land use maps to assess human drivers of change. Using an
automated classification approach with subpixel unmixing, we classified water
extent in nearly 1700 man-made lakes, or tanks, in Landsat images from 1973
to 2010. The classification results compared well with a reference dataset of
water extent of tanks (R2 = 0.95). We modeled the water extent of
42 clusters of tanks in a multiple regression on simple hydrological
covariates (including precipitation) and time.
Inter-annual variability in precipitation accounted for 63 % of the
predicted variability in water extent. However, precipitation did not exhibit
statistically significant trends in any part of the watershed. After
controlling for precipitation variability, we found statistically significant
temporal trends in water extent, both positive and negative, in 13 of the
clusters. Based on a water balance argument, we inferred that these trends
likely reflect a non-stationary relationship between precipitation and
watershed runoff. Independently of precipitation, water extent increased in a
region downstream of Bangalore, likely due to increased urban effluents, and
declined in the northern portion of the Arkavathy. Comparison of the drying
trends with land use indicated that they were most strongly associated with
irrigated agriculture, sourced almost exclusively by groundwater. This
suggests that groundwater abstraction was a major driver of hydrological
change in this watershed. Disaggregating the watershed-scale hydrological
response via remote sensing of surface water bodies over multiple decades
yielded a spatially resolved characterization of hydrological change in an
otherwise poorly monitored watershed. This approach presents an opportunity
to understand hydrological change in heavily managed watersheds where surface
water bodies integrate upstream runoff and can be delineated using satellite
imagery.