摘要：Soil water storage dynamics link landscape and climate processes with consequent impacts on hydrologic and biogeochemical cycles, and on ecosystem functions. We explore regional‐scale, spatiotemporal dynamics of root‐zone soil water storage using spatially explicit, long‐term simulations from a land data assimilation system over an area of ∼2 million km 2 in the U.S. Midwest. We synthesize the dataset to examine spatial patterns of hydroclimatic forcing and soil and vegetation properties to identify the key drivers of soil water storage across the region. To identify differences in temporal hydrologic variability between sites with different soil and vegetation characteristics, we focus on daily data from 10 locations, representative of three major land cover types in the region. We use the concepts of (a) soil water memory to evaluate differences in landscape buffering of rainfall and (b) persistence to evaluate the threshold‐crossing properties of statistically defined “wet” and “dry” soil water conditions. Power spectral analyses of soil water storage reveal that regionally consistent patterns emerge in memory at multiple temporal scales. Threshold‐crossing analyses reveal corresponding similarity in persistence between sites. The analyses show that stochastic rainfall is the key driver of landscape hydrologic dynamics, with rainfall frequency as the primary determinant of persistence across the region, whereas differences in land cover and soil properties across the region have second‐order influence. The synthesis approach we present here is useful for ecological and agricultural risk assessments of climate change impacts, including increasing frequency of extreme events such as droughts and floods, but primarily points to the need for better understanding of future precipitation changes.
关键词：ACF; autocorrelation function; ET; evapotranspiration; GVF; green vegetation fraction; LDAS; land data assimilation system; LIS; land information system; LULC; land use/land cover; NLDAS-2; Phase 2 of the North American Land Data Assimilation System; pdf; probability density function; PET; potential evapotranspiration.
