标题：Assessment of Runoff Sensitivity in the Upper Indus Basin to Interannual Climate Variability and Potential Change Using MODIS Satellite Data Products
摘要：The Upper Indus Basin (UIB) covers an area of more than 200,000 km2 and has an elevation range from below 1000 to over 8000 m above sea level. Its water resources underpin Pakistan's food security and energy supply. Vertical and horizontal variations in key climate variables govern the runoff contributions of the UIB's various elevation zones and subcatchments. Remote sensing climatic data products from NASA's Moderate Resolution Imaging Spectrometer (MODIS) instrument platform provide an opportunity to develop a spatial characterization of the climatology of remote and rugged regions such as the UIB. Specifically, snow-covered area (SCA) and land surface temperature (LST) have been shown to provide good analogues, respectively, for precipitation and air temperature. As such, SCA and LST quantify regional variations in mass and energy inputs to runoff generation processes. Although the 10-year (2000–2010) MODIS observational record is not adequate to evaluate long-term trends, it does provide a consistent depiction of annual cycles and a preliminary assessment of interannual variability. This study presents a summary of the period means and interannual variability found in remotely sensed SCA and LST products for the UIB. It then provides an update of locally observed recent climate trends for the 1962 to 2007 period. Nonparametric trend tests are applied both to the local observations and to remote sensing records to assess patterns in recent variability. The climatic noise (intense variability) of the past decade, however, renders conclusions on nascent trends in SCA and LST premature. Finally, runoff sensitivity to temperature change—spatially applied as summer (JJA) nighttime 0°C LST isotherm migration—is assessed for a range of potential scenarios. Results indicate that changes in mean summer (JJA) runoff could range from −30 to 35% or more, depending on whether recent locally observed changes continue or scenarios derived from current regional climate model (RCM) simulations unfold.
