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Abstract Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration (ET) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulateETisotope values (δET) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulatingδETvalues consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest (x‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes.
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Multi-variable, multi-configuration testing of ORCHIDEE land surface model water flux and storage estimates across semi-arid sites in the southwestern US
Abstract. Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydrological parameters; and (2) a 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations against daily and monthly soil moisture and ET observations, together with data-derived transpiration / evaporation, T / ET, ratios, from six semi-arid grass, shrub and forest sites in the southwestern USA. The 11-layer scheme also has modified calculations of surface runoff, bare soil evaporation, and water limitation to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fraction. We found that the more mechanistic 11-layer model results better representation of the daily and monthly ET observations. We show that is likely because of improved simulation of soil moisture in the upper layers of soil (top 5 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development. Adding a soil resistance term generally decreased simulated E and increased soil moisture content, thus increasing T and T / ET ratios and reducing the negative T / ET model-data bias. By reducing the bare soil fraction in the model, we illustrated that modelled leaf T is too low at sparsely vegetated sites. We conclude that a discretized soil hydrology scheme and associated developments improves estimates of ET by allowing the model to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from bare soil evaporation is not solved by this modification alone.
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- Award ID(s):
- 1655499
- PAR ID:
- 10274501
- Date Published:
- Journal Name:
- Hydrology and Earth System Sciences Discussions
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5194/hess-2019-598
