ALBERT

Description: Temporal water storage is a fundamental component of the terrestrial water cycle. Methods of estimating water storage variations are often limited to specific, well-monitored locations, and/or system scales. Thus, measures of storage from small systems can be difficult to compare to large systems. Here we compare three independent methods of estimating water storage variations for systems spanning over three orders of magnitude in basin area: 1) remote satellite observations (GRACE), 2) hydrograph recession curve analysis, and 3) quantifying precipitation-discharge hysteresis loops. We measured storage using all three methods for 242 watersheds in Asia (103 to 106 km2) and find that GRACE-derived storage correlates well with quantification of hysteresis terms but recession curve derived dynamic storage does not correlate with hysteresis terms or GRACE-derived storage. Thus, we argue that precipitation-discharge hysteresis may be able to be scaled to GRACE-derived storage as an independent estimate of storage for basins as small as 103 km2. Hysteresis-derived storage correlates well with mean monsoon rainfall in the upstream watershed while recession-derived dynamic storage does not. This suggests that hysteresis- and GRACE-derived storage may be input limited. In contrast, recession-derived dynamic storage does not correlate with topographic, climatic, or land cover metrics, suggesting that it may be limited by the rate at which water infiltrates into deep groundwater and then enters the river system. In addition, we find that recession-derived dynamic storage is a factor of seven lower than hysteresis-derived storage. We infer that hysteresis-derived storage includes recession curve-derived storage in addition to other storage units, such as snowpack, lakes, and soil moisture. Recession-derived dynamic storage in turn represents the annual variability in deep groundwater storage, a “leaky bucket” that is recharged from the top and “leaks” into rivers from deeper storage. These data may be able to be used to better quantify storage terms in hydrologic modeling.