Precipitation is the primary driver of hydrological models, and its spatial and temporal variability have a great impact on water partitioning. However, in data‐sparse regions, uncertainty in precipitation estimates is high and the sensitivity of water partitioning to this uncertainty is unknown. This is a particular challenge in drylands (semi‐arid and arid regions) where the water balance is highly sensitive to rainfall, yet there is commonly a lack of in situ rain gauge data. To understand the impact of precipitation uncertainty on the water balance in drylands, here we have performed simulations with a process‐based hydrological model developed to characterize the water balance in arid and semi‐arid regions (DRYP: DRYland water Partitioning model). We performed a series of numerical analyses in the Upper Ewaso Ng'iro basin, Kenya driven by three gridded precipitation datasets with different spatio‐temporal resolutions (IMERG, MSWEP, and ERA5), evaluating simulations against streamflow observations and remotely sensed data products of soil moisture, actual evapotranspiration, and total water storage. We found that despite the great differences in the spatial distribution of rainfall across a climatic gradient within the basin, DRYP shows good performance for representing streamflow (KGE >0.6), soil moisture, actual evapotranspiration, and total water storage (
- Award ID(s):
- 2039228
- NSF-PAR ID:
- 10351972
- Date Published:
- Journal Name:
- PeerJ
- Volume:
- 9
- ISSN:
- 2167-8359
- Page Range / eLocation ID:
- e12137
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract r >0.5). However, the choice of precipitation datasets greatly influences surface (infiltration, runoff, and transmission losses) and subsurface fluxes (groundwater recharge and discharge) across different climatic zones of the Ewaso Ng'iro basin. Within humid areas, evapotranspiration does not show sensitivity to the choice of precipitation dataset, however, in dry lowland areas it becomes more sensitive to precipitation rates as water‐limited conditions develop. The analysis shows that the highest rates of precipitation produce high rates of diffuse recharge in Ewaso uplands and also propagate into runoff, transmission losses and, ultimately focused recharge, with the latter acting as the main mechanism of groundwater recharge in low dry areas. The results from this modelling exercise suggest that care must be taken in selecting forcing precipitation data to drive hydrological modelling efforts, especially in basins that span a climatic gradient. These results also suggest that more effort is required to reduce uncertainty between different precipitation datasets, which will in turn result in more consistent quantification of the water balance. -
more » « less
Abstract For evaluating the climatic and landscape controls on long‐term baseflow, baseflow index (BFI, defined as the ratio of baseflow to streamflow) and baseflow coefficient (BFC, defined as the ratio of baseflow to precipitation) are formulated as functions of climate aridity index, storage capacity index (defined as the ratio of average soil water storage capacity to precipitation), and a shape parameter for the spatial variability of storage capacity. The derivation is based on the two‐stage partitioning framework and a cumulative distribution function for storage capacity. Storage capacity has a larger impact on BFI than on BFC. When storage capacity index is smaller than 1, BFI is less sensitive to storage capacity index in arid regions compared to that in humid regions; whereas, when storage capacity index is larger than 1, BFI is less sensitive to storage capacity index in humid regions. The impact of storage capacity index on BFC is only significant in humid regions. The shape parameter plays an important role on fast flow generation at the first‐stage partitioning in humid regions and baseflow generation at the second‐stage partitioning in arid regions. The derived formulae were applied to more than 400 catchments where storage capacity index was found to follow a logarithmic function with climate aridity index. The role of climate forcings at finer timescales on baseflow were quantified, indicating that seasonality in climate forcings has a significant control especially on BFI.
-
more » « less
Abstract Free‐living nematodes are one of the most diverse metazoan taxa in terrestrial ecosystems and are critical to the global soil carbon (C) cycling through their role in organic matter decomposition. They are highly dependent on water availability for movement, feeding, and reproduction. Projected changes in precipitation across temporal and spatial scales will affect free‐living nematodes and their contribution to C cycling with unforeseen consequences. We experimentally reduced and increased growing season precipitation for 2 years in 120 field plots at arid, semiarid, and mesic grasslands and assessed precipitation controls on nematode genus diversity, community structure, and C footprint. Increasing annual precipitation reduced nematode diversity and evenness over time at all sites, but the mechanism behind these temporal responses differed for dry and moist grasslands. In arid and semiarid sites, there was a loss of drought‐adapted rare taxa with increasing precipitation, whereas in mesic conditions increases in the population of predaceous taxa with increasing precipitation may have caused the observed reductions in dominant colonizer taxa and yielded the negative precipitation–diversity relationship. The effects of temporal changes in precipitation on all aspects of the nematode C footprint (respiration, production, and biomass C) were all dependent on the site (significant spatial × temporal precipitation interaction) and consistent with diversity responses at mesic, but not at arid and semiarid, grasslands. These results suggest that free‐living nematode biodiversity and their C footprint will respond to climate change‐driven shifts in water availability and that more frequent extreme wet years may accelerate decomposition and C turnover in semiarid and arid grasslands.
-
more » « less
Abstract As drought variability increases in forests around the globe, it is critical to evaluate and understand ecosystem attributes that ameliorate drought impacts. Trees in arid and semi‐arid ecosystems can sustain tree growth and transpiration during drought by accessing shallow groundwater, yet the extent to which groundwater influences forest growth and transpiration in humid environments has largely been unexplored. We quantified groundwater's influence on tree growth and transpiration in northern humid forests with sandy soils. We hypothesized that even in wet regions, soil droughts occur relatively frequently in forests with sandy soils and result in water stress and reduced tree growth. Further, we hypothesized these reductions in productivity are ameliorated if the forest can access shallow groundwater during dry conditions. We evaluated tree growth responses using tree cores in
Pinus resinosa -
more » « less
Plant communities and fungi inhabiting their phyllospheres change along precipitation gradients and often respond to changes in land use. Many studies have focused on the changes in foliar fungal communities on specific plant species, however, few have addressed the association between whole plant communities and their phyllosphere fungi. We sampled plant communities and associated phyllosphere fungal communities in native prairie remnants and post-agricultural sites across the steep precipitation gradient in the central plains in Kansas, USA. Plant community cover data and MiSeq ITS2 metabarcode data of the phyllosphere fungal communities indicated that both plant and fungal community composition respond strongly to mean annual precipitation (MAP), but less so to land use (native prairie remnants vs. post-agricultural sites). However, plant and fungal diversity were greater in the native remnant prairies than in post-agricultural sites. Overall, both plant and fungal diversity increased with MAP and the communities in the arid and mesic parts of the gradient were distinct. Analyses of the linkages between plant and fungal communities (Mantel and Procrustes tests) identified strong correlations between the composition of the two. However, despite the strong correlations, regression models with plant richness, diversity, or composition (ordination axis scores) and land use as explanatory variables for fungal diversity and evenness did not improve the models compared to those with precipitation and land use (ΔAIC < 2), even though the explanatory power of some plant variables was greater than that of MAP as measured by R2. Indicator taxon analyses suggest that grass species are the primary taxa that differ in the plant communities. Similar analyses of the phyllosphere fungi indicated that many plant pathogens are disproportionately abundant either in the arid or mesic environments. Although decoupling the drivers of fungal communities and their composition – whether abiotic or host-dependent – remains a challenge, our study highlights the distinct community responses to precipitation and the tight tracking of the plant communities by their associated fungal symbionts.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7717/peerj.12137
