5.4 MODIS and the AO in flood forecasting
High interannual variability in timing and rate of peak snow cover
depletion appear to modulate flooding occurrence, intensity and timing
in eastern Kazakhstan. Specific flood reports for the study area are
lacking, but figures from the Emergency Events Database (Guha-Sapir et
al., 2018) and Global Active Archive of Large Flood Events (Dartmouth
Flood Observatory, 2018) point to snowmelt-induced floods occurring
throughout Kazakhstan in 2008, 2010, 2011, 2015 and 2017 (Fig.5).
Comparison with peak PSCDR shows a general agreement, with the highest
peak snowmelt rates in the 18 year series occurring in 2011 and 2017. In
particular, severe flooding affecting the Uba basin in mid-April 2011
was reported on the official government news website (Dixinews, 2011),
corresponding with the timing of the highest PSCDR in the Uba basin in
the study period (Figs. 4 and 5). However, the third highest PSCDR in
2006 has no correspondence in flooding, although this might be due to a
bias towards better reporting in more recent years (both databases are
based on local news). Broad agreement is also seen with respect to
timing, with floods occurring relatively late in 2011, 2015 and 2017
(end of March –beginning of spring) and early in 2008 (20th February,
Dartmouth Flood Observatory, 2018), corresponding with late and early
values of DSCD (Fig. 7). Flood occurrence in 2010 however is reported as
early as March, in spite of very late peak snow cover depletion found in
our study. 2010 was a particularly cold winter with record snowfalls
(Cohen et al, 2010), and temperature increase above the snow melting
point at low elevations might have led to abundant snow melt and
subsequent flooding.
In spite of this general agreement, quantitative assessment of the
predictive ability of snow cover depletion maps based on MODIS and of
the possible use of the AO in flood forecasting in the Upper Irtysh
catchment is complicated by a lack of in situ observations in the study
area. To improve the ground-based hydrological monitoring network in
Kazakhstan, runoff should ideally be measured at stations, located in
the smaller, non-transboundary basins upstream of Bukhtarma reservoir.
In principle, the timing of flooding could could also be investigated
via remote sensing, by detecting flooded areas through optical
(Revilla-Romero et al., 2015) or SAR (Brown et al., 2016) satellite
images, and algorithms have also been devised to estimate discharge from
MODIS images based on the reflectance difference between water and land
pixels in near infrared bands (Tarpanelli et al., 2017). Validation of
these approaches in sparsely gauged catchments however remains a non
trivial task. Since our approach is based on readily available data, in
areas where ground based observations do exist, it could be more easily
validated, providing a means to evaluate MODIS DPSCD and PSCDR products
with respect to water management strategies and possibly implement
long-term forecasts based on the AO.