Opportunities from Remote Sensing for Supporting Water Resources Management in Village/Valley Scale Catchments in the Upper Indus Basin

Now and in the future, the flows of the Upper Indus Basin (UIB) are and will be depended upon by hundreds of millions of people for their food security and economic livelihoods. Communities in the headwater reaches of the UIB—which contribute the bulk of runoff for the basin—are equally deserving of improved living conditions, but often lag behind downstream communities in benefitting from infrastructure. Harsh and highly variable climatic conditions pose specific challenges for local agricultural activities in the headwater reaches. Improved scientific understanding of tributary basin scale hydrology should support local development work as well as improvements to large scale infrastructure and water resource management. This study focuses on the challenge of providing meaningful quantitative information at the village/valley scale in the upper reaches of the UIB. The typology of the UIB hydrological regimes—as observed in large gauged basins—are examined, with special emphasis on annual cycles and interannual variability. Variations in river flows (as relative anomalies of discharge rates or runoff) are compared to observations of climate parameters (2 m air temperature, precipitation) from both local (point-based) observations and analogous parameters from remote sensing data products from the MODIS instrument. Although the temporal overlap is limited between river gauging data available to this study and the MODIS observational record, numerical analysis of relationships between relative anomalies in the spatial data and river gauging observations demonstrate promising potential of the former to serve as quantitative indicators of runoff anomalies. In order to translate these relationships to the scale of ungauged village/valley catchments, the available remotely sensed spatial data—snow covered area (SCA), land surface temperature derived (LST)—are assessed as analogues for meteorological point observations. The correlations between local (point-based) observations and remotely-sensed spatial data products are tested across a wide range of spatial aggregations. These spatial units range from the primary contributing area (nearly 200,000 km 2 ) of the UIB at its downstream gauging station Besham to a small valley serving a minor settlement (10 km 2 ). The shape and timing of annual cycles in SCA and LST are consistent across the range of spatial scales although the magnitudes of both intra-annual and interannual variability differ with both spatial scale and hydrological regime. The interannual variability exhibited by these spatial data products is then considered in terms of its potential implications for the smaller hydrological units. Opportunities for improvement and extension of this methodology are also discussed. Copyright Springer Science+Business Media B.V. 2012