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Article: BASIN-3D: A brokering framework to integrate diverse environmental data

Varadharajan, Charuleka / Hendrix, Valerie C. / Christianson, Danielle S. / Burrus, Madison / Wong, Catherine / Hubbard, Susan S. / Agarwal, Deborah A.

Elsevier Ltd Computers & geosciences. 2022 Feb., v. 159

2022

Abstract: Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, ... ...

Abstract	Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, particularly due to differences in the structure and formats of data provided by various sources. Here, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a data integration framework designed to dynamically retrieve and transform heterogeneous data from different sources into a common format to provide an integrated view. BASIN-3D enables users to adopt a standardized approach for data retrieval and avoid customizations for the data type or source. We demonstrate the value of BASIN-3D with two use cases that require integration of data from regional to watershed spatial scales. The first application uses the BASIN-3D Python library to integrate time-series hydrological and meteorological data to provide standardized inputs to analytical and machine learning codes in order to predict the impacts of hydrological disturbances on large river corridors of the United States. The second application uses the BASIN-3D Django framework to integrate diverse time-series data in a mountainous watershed in East River, Colorado, United States to enable scientific researchers to explore and download data through an interactive web portal. Thus, BASIN-3D can be used to support data integration for both web-based tools, as well as data analytics using Python scripting and extensions like Jupyter notebooks. The framework is expected to be transferable to and useful for many other field and modeling studies.
Keywords	Internet ; Python ; computer software ; data collection ; ecosystems ; environmental science ; hydrology ; meteorological data ; mountains ; rivers ; time series analysis ; watersheds ; Colorado
Language	English
Dates of publication	2022-02
Publishing place	Elsevier Ltd
Document type	Article
ISSN	0098-3004
DOI	10.1016/j.cageo.2021.105024
Database	NAL-Catalogue (AGRICOLA)

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Article: Estimation of soil classes and their relationship to grapevine vigor in a Bordeaux vineyard: advancing the practical joint use of electromagnetic induction (EMI) and NDVI datasets for precision viticulture

Hubbard, Susan S. / Schmutz, Myriam / Balde, Abdoulaye / Falco, Nicola / Peruzzo, Luca / Dafflon, Baptiste / Léger, Emmanuel / Wu, Yuxin

Precision agriculture. 2021 Aug., v. 22, no. 4

2021

Abstract: Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and ... ...

Abstract	Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p < 0.01) was revealed between the geophysically-identified Bordeaux soil classes and NDVI (both 2 m resolution), showing that the highest grapevine vigor was associated with the Bordeaux soil classes having the largest clay fraction. The results suggest that within-block variability of grapevine vigor was largely controlled by variability in soil classes, and that carefully collected EMI and NDVI datasets can be exceedingly helpful for providing quantitative estimates of vineyard soil and vigor variability, as well as their covariation. The method is expected to be transferable to other viticultural regions, providing an approach to use easy-to-acquire, high resolution datasets to guide viticultural practices, including routine management and replanting.
Keywords	Vitis ; clay fraction ; data collection ; geophysics ; normalized difference vegetation index ; precision agriculture ; soil texture ; tomography ; vigor ; vineyard soils ; vineyards ; viticulture ; France
Language	English
Dates of publication	2021-08
Size	p. 1353-1376.
Publishing place	Springer US
Document type	Article
ZDB-ID	1482656-2
ISSN	1385-2256
ISSN	1385-2256
DOI	10.1007/s11119-021-09788-w
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Article: Variability in observed stable water isotopes in snowpack across a mountainous watershed in Colorado

Carroll, Rosemary W. H. / Deems, Jeffery / Maxwell, Reed / Sprenger, Matthias / Brown, Wendy / Newman, Alexander / Beutler, Curtis / Bill, Markus / Hubbard, Susan S. / Williams, Kenneth H.

Hydrological processes. 2022 Aug., v. 36, no. 8

2022

Abstract: Isotopic information from 81 snowpits was collected over a 5‐year period in a large, Colorado watershed. Data spans gradients in elevation, aspect, vegetation, and seasonal climate. They are combined with overlapping campaigns for water isotopes in ... ...

Abstract	Isotopic information from 81 snowpits was collected over a 5‐year period in a large, Colorado watershed. Data spans gradients in elevation, aspect, vegetation, and seasonal climate. They are combined with overlapping campaigns for water isotopes in precipitation and snowmelt, and a land‐surface model for detailed estimates of snowfall and climate at sample locations. Snowfall isotopic inputs, describe the majority of δ¹⁸O snowpack variability. Aspect is a secondary control, with slightly more enriched conditions on east and north facing slopes. This is attributed to preservation of seasonally enriched snowfall and vapour loss in the early winter. Sublimation, expressed by decreases in snowpack d‐excess in comparison to snowfall contributions, increases at low elevation and when seasonal temperature and solar radiation are high. At peak snow accumulation, post‐depositional fractionation appears to occur in the top 25 ± 14% of the snowpack due to melt‐freeze redistribution of lighter isotopes deeper into the snowpack and vapour loss to the atmosphere during intermittent periods of low relative humidity and high windspeed. Relative depth of fractionation increases when winter daytime temperatures are high and winter precipitation is low. Once isothermal, snowpack isotopic homogenization and enrichment was observed with initial snowmelt isotopically depleted in comparison to snowpack and enriching over time. The rate of δ¹⁸O increase (d‐excess decrease) in snowmelt was 0.02‰ per day per 100‐m elevation loss. Isotopic data suggests elevation dictates snowpack and snowmelt evolution by controlling early snow persistence (or absence), isotopic lapse rates in precipitation and the ratio of energy to snow availability. Hydrologic tracer studies using stable water isotopes in basins of large topographic relief will require adjustment for these elevational controls to properly constrain stream water sourcing from snowmelt.
Keywords	altitude ; climate ; energy ; evolution ; fractionation ; homogenization ; hydrology ; models ; mountains ; relative humidity ; snow ; snowmelt ; snowpack ; solar radiation ; streams ; sublimation ; temperature ; vapors ; vegetation ; watersheds ; wind speed ; winter ; Colorado
Language	English
Dates of publication	2022-08
Publishing place	John Wiley & Sons, Inc.
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	1479953-4
ISSN	1099-1085 ; 0885-6087
ISSN (online)	1099-1085
ISSN	0885-6087
DOI	10.1002/hyp.14653
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Article ; Online: Prolonged Drought in a Northern California Coastal Region Suppresses Wildfire Impacts on Hydrology

Newcomer, Michelle E. / Underwood, Jennifer / Murphy, Sheila F. / Ulrich, Craig / Schram, Todd / Maples, Stephen R. / Peña, Jasquelin / Siirila‐Woodburn, Erica R. / Trotta, Marcus / Jasperse, Jay / Seymour, Donald / Hubbard, Susan S.

Water Resources Research. 2023 Aug., v. 59, no. 8 p.e2022WR034206-

2023

Abstract: Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e., ...

Abstract	Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e., burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought‐prone, wildfire‐adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub‐watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre‐and‐post wildfire hydrology with a rainfall‐runoff hydrological model. Even though these successive wildfires burned 1%–50% of each sub‐watershed (1%–30% at moderate/high severity), we found little evidence of wildfire‐related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations—model simulations). Our findings that post‐wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.
Keywords	coasts ; drainage ; drought ; ecosystems ; forests ; hydrologic models ; research ; rivers ; runoff ; storms ; stream flow ; subwatersheds ; wildfires ; California
Language	English
Dates of publication	2023-08
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	5564-5
ISSN	1944-7973 ; 0043-1397
ISSN (online)	1944-7973
ISSN	0043-1397
DOI	10.1029/2022WR034206
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Article: Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed

Tran, Anh Phuong / Dafflon, Baptiste / Faybishenko, Boris / Hubbard, Susan S / Rungee, Joseph

Water. 2019 Jan. 31, v. 11, no. 2

2019

Abstract: Evapotranspiration (ET) is a key component of the water balance, which influences hydrometeorology, water resources, carbon and other biogeochemical cycles, and ecosystem diversity. This study aims to investigate the spatio-temporal variations of ET at ... ...

Abstract	Evapotranspiration (ET) is a key component of the water balance, which influences hydrometeorology, water resources, carbon and other biogeochemical cycles, and ecosystem diversity. This study aims to investigate the spatio-temporal variations of ET at the East River watershed in Colorado and analyze the factors that control these variations. ET was acquired using the community land model (CLM) simulations and was compared with the values estimated using Fu’s equation and a watershed-scale water balance equation. The simulation results showed that 55% of annual precipitation in the East River is lost to ET, in which 75% of the ET comes from the summer months (May to September). We also found that the contribution of transpiration to the total ET was ~50%, which is much larger than that of soil evaporation (32%) and canopy evaporation (18%). Spatial analysis indicated that the ET is greater at elevations of 2950–3200 m and lower along the river valley (<2750 m) and at the high elevations (>3900 m). A correlation analysis of factors affecting ET showed that the land elevation, air temperature, and vegetation are closely correlated and together they govern the ET spatial variability. The results also suggested that ET in areas with more finely textured soil is slightly larger than regions with coarse-texture soil. This study presents a promising approach to the assessment of ET with a high spatiotemporal resolution over watershed scales and investigates factors controlling ET spatiotemporal variations.
Keywords	air temperature ; altitude ; atmospheric precipitation ; biogeochemical cycles ; canopy ; carbon ; ecosystems ; equations ; evaporation ; evapotranspiration ; hydrometeorology ; models ; mountains ; river valleys ; rivers ; soil ; spatial variation ; summer ; temporal variation ; transpiration ; vegetation ; watersheds ; Colorado
Language	English
Dates of publication	2019-0131
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2521238-2
ISSN	2073-4441
ISSN	2073-4441
DOI	10.3390/w11020243
Database	NAL-Catalogue (AGRICOLA)

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Article: High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Wainwright, Haruko M. / Oktem, Rusen / Dafflon, Baptiste / Dengel, Sigrid / Curtis, John B. / Torn, Margaret S. / Cherry, Jessica / Hubbard, Susan S.

Land. 2021 July 09, v. 10, no. 7

2021

Abstract: Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem ... ...

Abstract	Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.
Keywords	automation ; carbon ; data collection ; land ; net ecosystem exchange ; permafrost ; tundra
Language	English
Dates of publication	2021-0709
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2682955-1
ISSN	2073-445X
ISSN	2073-445X
DOI	10.3390/land10070722
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Article: Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling

Tran, Anh Phuong / Dafflon, Baptiste / Bisht, Gautam / Hubbard, Susan S

Journal of hydrology. 2018 June, v. 561

2018

Abstract: Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydrobiochemical processes. This study jointly ... ...

Abstract	Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydrobiochemical processes. This study jointly interprets electrical resistivity tomography (ERT) measurements and hydro-thermal numerical simulation results to assess spatiotemporal variations of TLT and to determine its controlling factors in Barrow, Alaska. Time-lapse ERT measurements along a 35-m transect were autonomously collected from 2013 to 2015 and inverted to obtain soil electrical resistivity. Based on several probe-based TLT measurements and co-located soil electrical resistivity, we estimated the electrical resistivity thresholds associated with the boundary between the thaw layer and permafrost using a grid search optimization algorithm. Then, we used the obtained thresholds to derive the TLT from all soil electrical resistivity images. The spatiotemporal analysis of the ERT-derived TLT shows that the TLT at high-centered polygons (HCPs) is smaller than that at low-centered polygons (LCPs), and that both thawing and freezing occur earlier at the HCPs compared to the LCPs. In order to provide a physical explanation for dynamics in the thaw layer, we performed 1-D hydro-thermal simulations using the community land model (CLM). Simulation results showed that air temperature and precipitation jointly govern the temporal variations of TLT, while the topsoil organic content (SOC) and polygon morphology are responsible for its spatial variations. When the topsoil SOC and its thickness increase, TLT decreases. Meanwhile, at LCPs, a thicker snow layer and saturated soil contribute to a thicker TLT and extend the time needed for TLT to freeze and thaw. This research highlights the importance of combination of measurements and numerical modeling to improve our understanding spatiotemporal variations and key controls of TLT in cold regions.
Keywords	air temperature ; algorithms ; cold zones ; electrical resistance ; freezing ; global warming ; hydrology ; mathematical models ; permafrost ; snow ; spatial variation ; temporal variation ; thawing ; tomography ; topsoil ; Alaska ; Arctic region
Language	English
Dates of publication	2018-06
Size	p. 751-763.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	0022-1694
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2018.04.028
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Article ; Online: Microbial Metagenomics Reveals Climate-Relevant Subsurface Biogeochemical Processes.

Long, Philip E / Williams, Kenneth H / Hubbard, Susan S / Banfield, Jillian F

Trends in microbiology

2016 Volume 24, Issue 8, Page(s) 600–610

Abstract: Microorganisms play key roles in terrestrial system processes, including the turnover of natural organic carbon, such as leaf litter and woody debris that accumulate in soils and subsurface sediments. What has emerged from a series of recent DNA ... ...

Abstract	Microorganisms play key roles in terrestrial system processes, including the turnover of natural organic carbon, such as leaf litter and woody debris that accumulate in soils and subsurface sediments. What has emerged from a series of recent DNA sequencing-based studies is recognition of the enormous variety of little known and previously unknown microorganisms that mediate recycling of these vast stores of buried carbon in subsoil compartments of the terrestrial system. More importantly, the genome resolution achieved in these studies has enabled association of specific members of these microbial communities with carbon compound transformations and other linked biogeochemical processes-such as the nitrogen cycle-that can impact the quality of groundwater, surface water, and atmospheric trace gas concentrations. The emerging view also emphasizes the importance of organism interactions through exchange of metabolic byproducts (e.g., within the carbon, nitrogen, and sulfur cycles) and via symbioses since many novel organisms exhibit restricted metabolic capabilities and an associated extremely small cell size. New, genome-resolved information reshapes our view of subsurface microbial communities and provides critical new inputs for advanced reactive transport models. These inputs are needed for accurate prediction of feedbacks in watershed biogeochemical functioning and their influence on the climate via the fluxes of greenhouse gases, CO2, CH4, and N2O.
Language	English
Publishing date	2016-08
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1158963-2
ISSN	1878-4380 ; 0966-842X
ISSN (online)	1878-4380
ISSN	0966-842X
DOI	10.1016/j.tim.2016.04.006
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Article: The Colorado East River Community Observatory Data Collection

Kakalia, Zarine / Varadharajan, Charuleka / Alper, Erek / Brodie, Eoin L. / Burrus, Madison / Carroll, Rosemary W. H. / Christianson, Danielle S. / Dong, Wenming / Hendrix, Valerie C. / Henderson, Matthew / Hubbard, Susan S. / Johnson, Douglas / Versteeg, Roelof / Williams, Kenneth H. / Agarwal, Deborah A.

Hydrological processes. 2021 June, v. 35, no. 6

2021

Abstract: The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow‐dominated watershed to study hydrobiogeochemical responses to ... ...

Abstract	The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow‐dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behaviour. The ER has both long‐term and spatially‐extensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross‐disciplinary process‐based investigations and modelling of watershed behaviour. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value‐added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within 5 years of collection, these datasets have revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over 70 ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.
Keywords	biogeochemistry ; climate ; data collection ; floodplains ; genomics ; information management ; issues and policy ; mountains ; riparian areas ; rivers ; snow ; topographic slope ; value added ; water ; watersheds ; Colorado ; Colorado River
Language	English
Dates of publication	2021-06
Publishing place	John Wiley & Sons, Inc.
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	1479953-4
ISSN	1099-1085 ; 0885-6087
ISSN (online)	1099-1085
ISSN	0885-6087
DOI	10.1002/hyp.14243
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Article ; Online: Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information

Chen, Jinsong / Hubbard, Susan S. / Williams, Kenneth H. / Ficklin, Darren L.

Water Resources Research. 2016 Mar., v. 52, no. 3 p.1881-1898

2016

Abstract: Long‐term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in ... ...

Abstract	Long‐term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small‐scale historical hydrological data with large‐scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long‐term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site‐specific watershed reactive transport models to predict how climate‐induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.
Keywords	Bayesian theory ; climate models ; climatic factors ; ecosystems ; floodplains ; groundwater ; hydrologic data ; prediction ; probability distribution ; research ; stream flow ; time series analysis ; uncertainty ; water table ; watersheds ; Colorado ; Colorado River
Language	English
Dates of publication	2016-03
Size	p. 1881-1898.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	5564-5
ISSN	1944-7973 ; 0043-1397
ISSN (online)	1944-7973
ISSN	0043-1397
DOI	10.1002/2015WR017777
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