The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability
of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset
at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated
hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations
were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed
discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated
reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images
covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of
hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring
and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study
watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time
scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and
floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to
changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite
unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation,
evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to
develop effective eco-environment management plans and strategies that address the consequences of climate changes.
Hao Chen and Wanchang Zhang, "Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China," Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 1042106 (Presented at SPIE Remote Sensing: September 12, 2017; Published: 2 November 2017); https://doi.org/10.1117/12.2278357.
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