Abstract. In drylands, characterised by water scarcity and frequent meteorological droughts, knowledge of soil moisture dynamics and its drivers (evapotranspiration, soil physical properties and the timing and sequencing of precipitation events) is fundamental to understanding changes in water availability to plants and human society, especially under a nonstationary climate. Given the episodic and stochastic nature of rainfall in drylands and the limited availability of data in these regions, we sought to explore what effects the temporal resolution of precipitation data has on soil moisture and how soil moisture distributions might evolve under different scenarios of climate change. Such information is critical for anticipating the impact of a changing climate on dryland communities across the globe, especially those that depend on rainfed agriculture and groundwater wells for drinking water for humans and livestock. A major challenge to understanding soil moisture in response to climate is the availability of precipitation datasets for dryland regions across the globe. Gridded precipitation data may only be available for daily or weekly time periods, even though rainstorms in drylands often occur on much shorter time scales, but it is currently unknown how this timescale mismatch might affect our understanding of soil moisture. Numerical modelling enables retrodiction or prediction of how climate translates into dynamically evolving moisture within the soil profile. It can be used to explore how climate data at different temporal resolutions affect these soil moisture dynamics, as well as to explore the influence of shifts in rainfall characteristics (e.g., storm intensity) under potential scenarios of climate change. This study uses Hydrus 1-D, to investigate the dynamics of soil moisture over a period of decades in response to the same underlying rainfall data resolved at hourly, daily, and weekly resolutions, as well as to step changes in rainfall delivery, which is expected under a warming atmosphere. We parameterised the model using rainfall, evaporative demand, and soils data from the semi-arid Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but we present the results as a generalized study of how rainfall resolution and shifts in rainfall intensity may affect dryland soil moisture at different depths. Our results indicate that hourly or better rainfall resolution captures the dynamics of soil moisture in drylands, and that critical information on soil water content, moisture availability to vegetation, actual evapotranspiration, and deep percolation of infiltrated water is lost when soil moisture modelling is driven by rainfall data at coarser temporal resolutions (daily, weekly). We further show that modest changes in rainfall intensity dramatically shift soil water content and the overall water balance. These findings are relevant to the prediction of soil moisture for crop yield forecasts, for adaptation to climate-related risks, and for anticipating the challenges of water scarcity and food insecurity in dryland communities around the globe, where available datasets are of low spatial and temporal resolution.
Climatic expression of rainfall on soil moisture dynamics in drylands
