skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Thursday, June 12 until 2:00 AM ET on Friday, June 13 due to maintenance. We apologize for the inconvenience.


Title: Using an Isotope Enabled Mass Balance to Evaluate Existing Land Surface Models
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.  more » « less
Award ID(s):
2309269 1802880
PAR ID:
10559032
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Water Resources Research
Volume:
60
Issue:
12
ISSN:
0043-1397
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    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. 
    more » « less
  2. Abstract Vegetation plays a crucial role in atmosphere‐land water and energy exchanges, global carbon cycle and basin water conservation. Land Surface Models (LSMs) typically represent vegetation characteristics by monthly climatological indices. However, static vegetation parameterization does not fully capture time‐varying vegetation characteristics, such as responses to climatic fluctuations, long‐term trends, and interannual variability. It remains unclear how the interaction between vegetation and climate variability propagates into hydrologic fluxes and water resources. Multi‐source satellite data sets may introduce uncertainties and require extensive time for analysis. This study developes a deep learning surrogate for a widely used LSM (i.e., Noah) as a rapid diagnosic tool. The calibrated surrogate quantifies the impacts of time‐varying vegetation characteristics from multiple remotely sensed GVF products on the magnitude, seasonality, and biotic and abiotic components of hydrologic fluxes. Using the Upper Colorado River Basin (UCRB) as a test case, we found that time‐varying vegetation provides more buffering effect against climate fluctuation than the static vegetation configuration, leading to reduced variability in the abiotic evaporation components (e.g., soil evaporation). In addition, time‐varying vegetation from multi‐source remote sensing products consistently predicts smaller biotic evaporation components (e.g., transpiration), leading to increased water yield in the UCRB (about 14%) compared to the static vegetation scheme. We also highlight the interaction between dynamic vegetation parameterization and static parameterization (e.g., soil) during calibration. Parameter recalibration and a re‐evaluation of certain model assumptions may be required for assessing climate change impacts on vegetation and basin‐wide water resources. 
    more » « less
  3. Partitioning evapotranspiration (ET) into its constituent fluxes (transpiration (T) and evaporation (E)) is important for understanding water use efficiency in forests and other ecosystems. Recent advancements in cavity ringdown spectrometers (CRDS) have made collecting high-resolution water isotope data possible in remote locations, but this technology has rarely been utilized for partitioning ET in forests and other natural systems. To understand how the CRDS can be integrated with more traditional techniques, we combined stable isotope, eddy covariance, and sap flux techniques to partition ET in an oak woodland using continuous water vapor CRDS measurements and monthly soil and twig samples processed using isotope ratio mass spectrometry (IRMS). Furthermore, we wanted to compare the efficacy of δ2H versus δ18O within the stable isotope method for partitioning ET. We determined that average daytime vapor pressure deficit and soil moisture could successfully predict the relative isotopic compositions of soil (δe) and xylem (δt) water, respectively. Contrary to past studies, δ2H and δ18O performed similarly, indicating CRDS can increase the utility of δ18O in stable isotope studies. However, we found a 41–49% overestimation of the contribution of T to ET (fT) when utilizing the stable isotope technique compared to traditional techniques (reduced to 4–12% when corrected for bias), suggesting there may be a systematic bias to the Craig-Gordon Model in natural systems. 
    more » « less
  4. null (Ed.)
    Abstract. The acceleration of urbanization requires sustainable, adaptive management strategies for land and water use in cities. Although the effects of buildings and sealed surfaces on urban runoff generation and local climate are well known, much less is known about the role of water partitioning in urban green spaces. In particular, little is quantitatively known about how different vegetation types of urban green spaces (lawns, parks, woodland, etc.) regulate partitioning of precipitation into evaporation, transpiration and groundwater recharge and how this partitioning is affected by sealed surfaces. Here, we integrated field observations with advanced, isotope-based ecohydrological modelling at a plot-scale site in Berlin, Germany. Soil moisture and sap flow, together with stable isotopes in precipitation, soil water and groundwater recharge, were measured over the course of one growing season under three generic types of urban green space: trees, shrub and grass. Additionally, an eddy flux tower at the site continuously collected hydroclimate data. These data have been used as input and for calibration of the process-based ecohydrological model EcH2O-iso. The model tracks stable isotope ratios and water ages in various stores (e.g. soils and groundwater) and fluxes (evaporation, transpiration and recharge). Green water fluxes in evapotranspiration increased in the order shrub (381±1mm) 
    more » « less
  5. The influence of the Unified Noah and Noah-MP land surface models (LSMs) on the evolution of cumulus clouds reaching convective initiation (CI) is assessed using infrared brightness temperatures (BT) from GOES-16. Cloud properties from individual cloud objects are examined using output from high-resolution (500 m horizontal grid spacing) model simulations. Cloud objects are tracked over time and related to observed clouds reaching CI to examine differences in cloud extent, longevity, and growth rate. The results demonstrate that differences in assumed surface properties can lead to large discrepancies in the net surface radiative budget, particularly in the sensible and latent heating components where differences exceed 40 W m−2. These differences lead to changes in the local mesoscale circulation patterns that are more pronounced near the edges of forested and grassland boundaries where lower-level convergence is stronger. Higher sensible heating from the Noah-MP LSM produced growth of CI clouds earlier and with increased longevity, which was closer to the timing and growth observed from GOES-16. The increased cloud growth in the Noah-MP experiment results from stronger and deeper updrafts, which lofts more cloud water into the upper levels of the troposphere. The weaker updrafts from the Noah LSM experiment results in shallower convection after CI is detected due to slower growth rates. The differences in cloud properties and growth are directly related to the land surfaces they develop above and point to the importance of accurately representing land properties and radiative characteristics when simulating convection in numerical weather prediction models. 
    more » « less