Modeling Subsurface Hydrology in Floodplains

Abstract

Soil‐moisture patterns in floodplains are highly dynamic, owing to the complex relationships between soil properties, climatic conditions at the surface, and the position of the water table. Given this complexity, along with climate change scenarios in many regions, there is a need for a model to investigate the implications of different conditions on water availability to riparian vegetation. We present a model, HaughFlow, which is able to predict coupled water movement in the vadose and phreatic zones of hydraulically connected floodplains. Model output was calibrated and evaluated at six sites in Australia to identify key patterns in subsurface hydrology. This study identifies the importance of the capillary fringe in vadose zone hydrology due to its water storage capacity and creation of conductive pathways. Following peaks in water table elevation, water can be stored in the capillary fringe for up to months (depending on the soil properties). This water can provide a critical resource for vegetation that is unable to access the water table. When water table peaks coincide with heavy rainfall events, the capillary fringe can support saturation of the entire soil profile. HaughFlow is used to investigate the water availability to riparian vegetation, producing daily output of water content in the soil over decadal time periods within different depth ranges. These outputs can be summarized to support scientific investigations of plant‐water relations, as well as in management applications.

Onset and propagation of drought into soil moisture and vegetation responses during the 2012–2019 drought in Southern California

“…Rather than attempting to model detailed soil moisture processes, we used a soil moisture balance model (SMBM), which is based on a simple 'bucket' approach established by the FAO (Allen et al, 1998), and is a variant of a code previously developed for estimating groundwater recharge (Cuthbert et al, 2013;. Simple modeling frameworks capable of linking vegetation to water availability can be useful tools to assess past and future ecohydrological dynamics in a range of water-limited environments (Caylor et al, 2009;D'Odorico et al, 2007;Evans et al, 2018;Quichimbo et al, 2020). Model inputs include information on soil properties, vegetation cover and climate (precipitation and the meteorological variables required to estimate evapotranspiration (PET) (Figure 3).…”

STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change

“…The WGEW example implemented for illustration of the model here is one such basin with a strong monsoon season that produces a high percentage of the annual rain and most of the runoff, compared with the winter season dominated by weak frontal storms. These improvements to STORM now make it suitable as a climate driver of other watershed response models that simulate hydrology between slopes and channels (surface runoff, infiltration, streamflow) Wainwright, 2002, 2008;Michaelides and Wilson, 2007), groundwater recharge during and after rainfall events (Beven and Freer, 2001), and interactions between streamflow and alluvial aquifers (Evans et al, 2018). It also enables STORM to be useful in water balance models (e.g., land surface models) to assess water availability to plants through dynamic ecohydrological simulation of plant-climate interactions and water utilization (D'Odorico et al, 2007;Caylor et al, 2006;Laio et al, 2006), as well as energy/carbon fluxes between the land surface and the atmosphere (Best et al, 2011;Bonan, 1996).…”

“…Coupling STORM to such models would enable a wide range of interdisciplinary scientists to investigate key problems in the environment that have their origin in the climate system. These range from which water sources are used by plants (Sargeant and Singer, 2016;Evaristo et al, 2015;Evaristo and McDonnell, 2017;Dawson and Ehleringer, 1991) to what is the dominant source and timing of groundwater recharge (Cuthbert et al, 2016;Wheater et al, 2010;Scanlon et al, 2006) to the role of climate in shaping landscape morphology (Singer and Michaelides, 2014;Tucker and Bras, 2000;Tucker and Slingerland, 1997;Michaelides et al, 2018). A version of STORM is under active development in the modular opensource surface process modeling framework Landlab (Hobley et al, 2017), in part to facilitate such future work.…”

Drought onset and propagation into soil moisture and grassland vegetation responses during the 2012–2019 major drought in Southern California

“…Although, the entire state experienced drought effects to some degree, there were notable differences in vegetation responses between Northern California and Southern California (Dong et al, 2019). In upland forests within the Sierra Nevada, there was large-scale canopy water loss and forest dieback as a result of the accumulated precipitation deficits, increased evaporative demand, and soil moisture drying (Asner et al, 2016;Fettig et al, 2019;Goulden and Bales, 2019), while there was only a documented decline in vegetation greenness in Southern California (Dong et al, 2019). Little is known about the propagation of drought from the atmosphere into soil moisture or its associated effects on vegetation in lowland areas, especially within water-limited regions where grasses and shrubs dominate the landscape.…”