| Title: | Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China |
| Authors: | Li, Z. and J. Jin |
| Year: | 2017 |
| Journal: | Hydrology and Earth System Sciences |
| Volume (Issue): | 21(11) |
| Pages: | 5531-5546 |
| Article ID: | |
| DOI: | 10.5194/hess-21-5531-2017 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | climate change |
| Secondary Application Category: | weather generator effects/processes |
| Watershed Description: | 45,421 km^2 Jing River, located in the Loess Plateau region in north central China. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Projected hydrological variability is important
for future resource and hazard management of water supplies
because changes in hydrological variability can cause
more disasters than changes in the mean state. However, climate
change scenarios downscaled from Earth System Models
(ESMs) at single sites cannot meet the requirements of
distributed hydrologic models for simulating hydrological
variability. This study developed multisite multivariate climate
change scenarios via three steps: (i) spatial downscaling
of ESMs using a transfer function method, (ii) temporal
downscaling of ESMs using a single-site weather generator,
and (iii) reconstruction of spatiotemporal correlations
using a distribution-free shuffle procedure. Multisite precipitation
and temperature change scenarios for 2011–2040 were
generated from five ESMs under four representative concentration
pathways to project changes in streamflow variability
using the Soil and Water Assessment Tool (SWAT) for
the Jing River, China. The correlation reconstruction method
performed realistically for intersite and intervariable correlation
reproduction and hydrological modeling. The SWAT
model was found to be well calibrated with monthly streamflow
with a model efficiency coefficient of 0.78. It was projected
that the annual mean precipitation would not change,
while the mean maximum and minimum temperatures would
increase significantly by 1.6 (+ or -0.3) and 1.3 (+ or -0.2) C; the variance
ratios of 2011–2040 to 1961–2005 were 1.15 (+ or -0.13)
for precipitation, 1.15 (+ or -0.14) for mean maximum temperature,
and 1.04 (+ or -0.10) for mean minimum temperature. A
warmer climate was predicted for the flood season, while
the dry season was projected to become wetter and warmer;
the findings indicated that the intra-annual and interannual
variations in the future climate would be greater than in the
current climate. The total annual streamflow was found to
change insignificantly but its variance ratios of 2011–2040
to 1961–2005 increased by 1.25 (+ or -0.55). Streamflow variability
was predicted to become greater over most months on
the seasonal scale because of the increased monthly maximum
streamflow and decreased monthly minimum streamflow.
The increase in streamflow variability was attributed
mainly to larger positive contributions from increased precipitation
variances rather than negative contributions from
increased mean temperatures. |
| Language: | English |
| Keywords: | |