scholarly journals A novel approach to partitioning evapotranspiration into evaporation and transpiration in flooded ecosystems

2021 ◽  
Author(s):  
Elke Eichelmann ◽  
Mauricio Cruz Mantoani ◽  
Samuel D. Chamberlain ◽  
Kyle S. Hemes ◽  
Patricia Y Oikawa ◽  
...  
Keyword(s):  
Friction Velocity ◽  
Water Cycle ◽  
Sensible Heat Flux ◽  
Open Water ◽  
Restored Wetlands ◽  
Average Value ◽  
Global Water Cycle ◽  
Novel Approach ◽  
Leaf Level ◽  
Input Variables

Reliable partitioning of micrometeorologically measured evapotranspiration (ET) into evaporation (E) and transpiration (T) would greatly enhance our understanding of the water cycle and its response to climate change. While some methods on ET partitioning have been developed, their underlying assumptions make them difficult to apply more generally, especially in sites with large contributions of E. Here, we report a novel ET partitioning method using Artificial Neural Networks (ANN) in combination with a range of environmental input variables to predict daytime E from nighttime ET measurements. The study uses eddy covariance data from four restored wetlands in the Sacramento-San Joaquin Delta, California, USA, as well as leaf-level T data for validation. The four wetlands vary in structure from some with large areas of open water and little vegetation to very densely vegetated wetlands, representing a range of ET conditions. The ANNs were built with increasing complexity by adding the input variable that resulted in the next highest average value of model testing R2 across all sites. The order of variable inclusion (and importance) was: vapor pressure deficit (VPD) > gap-filled sensible heat flux (H_gf) > air temperature (Tair) > friction velocity (u∗) > other variables. Overall, 36 ANNs were analyzed. The model using VPD, H_gf, Tair, and u∗ (F11), showed an average testing R2 value across all sites of 0.853. In comparison with the model that included all 10 variables (F36), F11 generally performed better during validation with independent data. In comparison to other methods described in the literature, the ANN method generated more consistent T/ET partitioning results especially for more complex sites with large E contributions. Our method improves the understanding of T/ET partitioning. While it may be particularly suited to flooded ecosystems, it can also improve T/ET partitioning in other systems, increasing our knowledge of the global water cycle.

The global water cycle and continental erosion during Phanerozoic time (570 my)

1989 ◽  
Vol 289 (4) ◽  
pp. 455-483 ◽  
Author(s):  
Y. Tardy ◽  
R. N'Kounkou ◽  
J.-L. Probst
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Continental Erosion ◽  
Global Water

scholarly journals Micropollutant-loaded powdered activated carbon released from waste water treatment plants: a risk for sediment-dwelling organisms?

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Marion Woermann ◽  
Julios Armand Kontchou ◽  
Bernd Sures
Keyword(s):  
Activated Carbon ◽  
Wastewater Treatment Plants ◽  
Water Cycle ◽  
Waste Water Treatment ◽  
Additional Treatment ◽  
Powdered Activated Carbon ◽  
Lumbriculus Variegatus ◽  
Negative Effects ◽  
Global Water Cycle ◽  
Receiving Waters

Abstract Background In order to protect aquatic environments and to reduce the presence of micropollutants in the global water cycle, wastewater treatment plants (WWTPs) often implement an additional treatment step. One of the most effective measures is the use of powdered activated carbon (PAC) as an adsorbent for micropollutants. This method provides sufficient elimination rates for several micropollutants and has been successfully employed in many WWTPs. Despite this success, there might be a drawback as the retention of the PAC in the WWTP can be challenging and losses of micropollutant-loaded PAC into the aquatic environment may occur. Upon emission, micropollutant-loaded PAC is expected to settle to the benthic zone of receiving waters, where sediment-dwelling organisms may ingest these particles. Therefore, the present study investigated possible adverse effects of micropollutant-loaded PAC from a WWTP as compared to unloaded (native) and diclofenac-loaded PAC on the sediment-dwelling annelid Lumbriculus variegatus. Results Native PAC induced the strongest effects on growth (measured as biomass) and reproduction of the annelids. The corresponding medium effective concentrations (EC50) were 1.7 g/kg and 1.8 g/kg, respectively. Diclofenac-loaded PAC showed lower effects with an EC50 of 2.5 g/kg for growth and EC50 of 3.0 g/kg for reproduction. Although tested at the same concentrations, the micropollutant-loaded PAC from the WWTP did not lead to obvious negative effects on the endpoints investigated for L.variegatus and only a slight trend of a reduced growth was detected. Conclusion We did not detect harmful effects on L. variegatus caused by the presence of MP-loaded PAC from a WWTP which gives an auspicious perspective for PAC as an advanced treatment option.

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

Self-validating deep learning of continental hydrology through satellite gravimetry and altimetry

2021 ◽  
Author(s):  
Christopher Irrgang ◽  
Jan Saynisch-Wagner ◽  
Robert Dill ◽  
Eva Boergens ◽  
Maik Thomas
Keyword(s):  
Neural Network ◽  
Satellite Altimetry ◽  
Water Cycle ◽  
Global Water Cycle ◽  
Network Training ◽  
The Neural Network ◽  
Continental Hydrology ◽  
Terrestrial Water ◽  
Combine Machine ◽  
Groundwater Basins

<p>Space-borne observations of terrestrial water storage (TWS) are an essential ingredient for understanding the Earth's global water cycle, its susceptibility to climate change, and for risk assessments of ecosystems, agriculture, and water management. However, the complex distribution of water masses in rivers, lakes, or groundwater basins remains elusive in coarse-resolution gravimetry observations. We combine machine learning, numerical modeling, and satellite altimetry to build and train a downscaling neural network that recovers simulated TWS from synthetic space-borne gravity observations. The neural network is designed to adapt and validate its training progress by considering independent satellite altimetry records. We show that the neural network can accurately derive TWS anomalies in 2019 after being trained over the years 2003 to 2018. Specifically for validated regions in the Amazonas, we highlight that the neural network can outperform the numerical hydrology model used in the network training.</p><p>https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL089258</p>

Multiscale Convective Organization and the YOTC Virtual Global Field Campaign

2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Building Blocks ◽  
Tropical Convection ◽  
Global Water Cycle ◽  
Weather And Climate ◽  
Impact Phenomena ◽  
Meteorological Systems ◽  
The Tropics

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.

scholarly journals Simulating the Effects of Land Surface Characteristics on Planetary Boundary Layer Parameters for a Modeled Landfalling Tropical Cyclone

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 138
Author(s):  
Yu Wang ◽  
Corene J. Matyas
Keyword(s):  
Tropical Cyclone ◽  
Land Surface ◽  
Friction Velocity ◽  
Inner Core ◽  
Sensible Heat Flux ◽  
Surface Characteristics ◽  
Near Surface ◽  
Land Surfaces ◽  
Rain Rates ◽  
Land Surface Characteristics

This study examined whether varying moisture availability and roughness length for the land surface under a simulated Tropical Cyclone (TC) could affect its production of precipitation. The TC moved over the heterogeneous land surface of the southeastern U.S. in the control simulation, while the other simulations featured homogeneous land surfaces that were wet rough, wet smooth, dry rough, and dry smooth. Results suggest that the near-surface atmosphere was modified by the changes to the land surface, where the wet cases have higher latent and lower sensible heat flux values, and rough cases exhibit higher values of friction velocity. The analysis of areal-averaged rain rates and the area receiving low and high rain rates shows that simulations having a moist land surface produce higher rain rates and larger areas of low rain rates in the TC’s inner core. The dry and rough land surfaces produced a higher coverage of high rain rates in the outer regions. Key differences among the simulations happened as the TC core moved over land, while the outer rainbands produced more rain when moving over the coastline. These findings support the assertion that the modifications of the land surface can influence precipitation production within a landfalling TC.

scholarly journals Quality assessment of water cycle parameters in REMO by Radar-Lidar synergy

2007 ◽  
Vol 7 (3) ◽  
pp. 8455-8524
Author(s):  
B. Hennemuth ◽  
A. Weiss ◽  
J. Bösenberg ◽  
D. Jacob ◽  
H. Linné ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Soil Moisture ◽  
Water Content ◽  
Water Vapour ◽  
Water Cycle ◽  
Sensible Heat Flux ◽  
Regional Model ◽  
Cloud Base ◽  
Cloud Radar

Abstract. A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better fit with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study. Rain rates are similar, but the representativeness of both observations and grid box values is low.

scholarly journals Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

2017 ◽  
Author(s):  
Gordon B. Bonan ◽  
Edward G. Patton ◽  
Ian N. Harman ◽  
Keith W. Oleson ◽  
John J. Finnigan ◽  
...  
Keyword(s):  
Heat Flux ◽  
Friction Velocity ◽  
Sensible Heat Flux ◽  
Roughness Sublayer ◽  
Sensible Heat ◽  
Area Index ◽  
Community Land Model ◽  
Diurnal Range ◽  
Radiative Temperature ◽  
Canopy Model

Abstract. Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multi-layer canopy model (CLM-ml v0) test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at 7 forest, 2 grassland, and 3 cropland AmeriFlux sites over a range of canopy height, leaf area index, and climate. The CLM4.5 has pronounced biases during summer months at forest sites in mid-day latent heat flux, sensible heat flux, and gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. The signature of the roughness sublayer is most evident in sensible heat flux, friction velocity, and the diurnal cycle of radiative temperature. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin–Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these short canopies. The multi-layer canopy with the roughness sublayer turbulence improves simulations compared with the CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

scholarly journals Ocean Salinities Reveal Strong Global Water Cycle Intensification During 1950 to 2000

Science ◽  
2012 ◽  
Vol 336 (6080) ◽  
pp. 455-458 ◽  
Author(s):  
P. J. Durack ◽  
S. E. Wijffels ◽  
R. J. Matear
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Global Water
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