Data-model comparison of temporal variability in long-term time series of large-scale soil moisture

Verrot, Lucile; Destouni, Georgia

doi:10.1002/2016jd025209

Cited by 10 publications

(7 citation statements)

References 66 publications

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“…Because this additional dampening effect is accounted for in ( σ R / σ P ), so is also the influence of lakes and wetlands on

\overset{P}{true}

partitioning (van der Velde, Lyon, & Destouni, ) and through that on ( σ R / σ P ). The

\overset{P}{true}

partitioning, and through that the dampening factor ( σ R / σ P ), may also be further affected by hydrological seasonality (Verrot & Destouni, ), long‐term changes in climate (van der Velde et al, ), and human land and water uses (Destouni, Jaramillo, & Prieto, ; Jaramillo & Destouni, ). In this study, we want to capture all possible influences on flow‐variability dampening due to lakes and wetlands and use therefore the standard deviation relation ( σ R / σ P ) as our primary comparative flow dampening factor.…”

Section: General Conceptual and Quantification Basismentioning

confidence: 99%

Large‐scale comparison of flow‐variability dampening by lakes and wetlands in the landscape

Quin

Destouni

2018

Land Degrad Dev

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Considering the potential of wetlands to dampen temporal variability of water flow through the landscape, they are increasingly considered as possible nature‐based solutions to mitigate risks of flooding and drought. In this study, we investigate flow variability by means of a flow dampening factor and use observation data from 1984 to 2013 for 82 Swedish catchments to statistically and comparatively analyze the large‐scale effects on this factor of multiple wetlands and lakes in the landscape. The results show good correlation between large‐scale flow dampening and relative area of lakes and floodplain wetlands within a catchment. An increase in relative area up to around 15% for lakes and 0.5% for floodplain wetlands lowers the temporal standard deviation of runoff (R) to around 10%–15% of that for precipitation (P), compared with a common flow‐variability dampening of around 35% for catchments with lake‐wetland area close to zero. Further increase in these relative areas, or in those of wetland types other than floodplain wetlands, has little or no flow dampening effect. The results indicate that the large‐scale flow dampening effect of lakes and floodplain wetlands is mainly due to their water‐storage capacity and less due to their possible effects on the partitioning of P between R and evapotranspiration. Overall, the results emphasize the importance of accounting for the problem scale and relative water‐storage capacity of wetlands when considering their large‐scale efficiency as possible nature‐based solutions for large‐scale flow‐variability regulation in whole catchments.

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“…Because this additional dampening effect is accounted for in ( σ R / σ P ), so is also the influence of lakes and wetlands on

\overset{P}{true}

partitioning (van der Velde, Lyon, & Destouni, ) and through that on ( σ R / σ P ). The

\overset{P}{true}

Section: General Conceptual and Quantification Basismentioning

confidence: 99%

Large‐scale comparison of flow‐variability dampening by lakes and wetlands in the landscape

Quin

Destouni

2018

Land Degrad Dev

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“…However, these effects are complex (Reichstein et al, 2013;Knapp et al, 2015;Bartlett et al, 2016), with the drought response of plants (partly) non-linearly depending on various factors. These comprise vegetation characteristics, such as root depth, leaf area, and plant physiology; soil characteristics, such as water holding capacity; and hydrological and terrain characteristics, which in turn affect groundwater level and thereby also soil moisture conditions above (Destouni and Verrot, 2014;Verrot and Destouni, 2016). Moreover, drought history can also play a role through legacy effects (Seneviratne et al, 2012a).…”

Section: Introductionmentioning

confidence: 99%

Large-scale biospheric drought response intensifies linearly with drought duration in arid regions

et al. 2020

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Abstract. Soil moisture droughts have comprehensive implications for terrestrial ecosystems. Here we study time-accumulated impacts of the strongest observed droughts on vegetation. The results show that drought duration, the time during which surface soil moisture is below seasonal average, is a key diagnostic variable for predicting drought-integrated changes in (i) gross primary productivity, (ii) evapotranspiration, (iii) vegetation greenness, and (iv) crop yields. Drought-integrated anomalies in these vegetation-related variables scale linearly with drought duration with a slope depending on climate. In arid regions, the slope is steep such that vegetation drought response intensifies with drought duration, whereas in humid regions, it is small such that drought impacts on vegetation are weak even for long droughts. These emergent large-scale linearities are not well captured by state-of-the-art hydrological, land surface, and vegetation models. Overall, the linear relationship of drought duration versus vegetation response and crop yield reductions can serve as a model benchmark and support drought impact interpretation and prediction.

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“…Accurate characterization of RZSM in land surface models, terrestrial biosphere models, and earth system models is critical for accurately estimating short‐term (hourly‐yearly), medium‐term (yearly‐to‐decadal), and long‐term (decadal‐to‐centennial) carbon, water, and energy fluxes. With regard to water fluxes, previous studies have shown that there are model‐dependent, systematic biases in model‐based estimates of soil moisture or RZSM when against ground observations (Koster et al, ; Loew et al, ; Pan et al, ; Verrot & Destouni, ; Xia et al, ) and remotely sensed measurements of near‐surface soil moisture (Gumuzzio et al, ; Polcher et al, ), and that models show divergent biases (van den Hurk et al, ). With respect to carbon fluxes, Kim et al () demonstrated the importance of soil moisture stress response functions for predictions of carbon fluxes in the Ent Terrestrial Biosphere Model.…”

Section: Introductionmentioning

confidence: 99%

The Sensitivity of North American Terrestrial Carbon Fluxes to Spatial and Temporal Variation in Soil Moisture: An Analysis Using Radar‐Derived Estimates of Root‐Zone Soil Moisture

et al. 2019

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This study examines the impact of variation in root-zone soil moisture (RZSM), a key component of the Earth's hydrologic cycle and climate system, on regional carbon fluxes across seven North American ecosystems. P-band synthetic aperture radar-derived RZSM estimates were incorporated into the ecosystem demography (ED2) terrestrial biosphere model through a model-data blending approach. Analysis shows that the model qualitatively captures inter-daily and seasonal variability of observed RZSM at seven flux tower sites (r = 0.59 ± 0.26 and r = 0.70 ± 0.22 for 0-10 and 10-40 cm of soil layers, respectively; P < 0.001). Incorporating the remotely sensed RSZM estimates increases the accuracy (root-mean-square deviations decrease from 0.10 ± 0.07 and 0.09 ± 0.06 m 3 ·m −3 to 0.08 ± 0.05 and 0.07 ± 0.03 m 3 ·m −3 for 0-10 and 10-40 cm of soil layers, respectively) of the model's RZSM predictions. The regional carbon fluxes predicted by the native and RZSM-constrained model were used to quantify sensitivities of gross primary productivity, autotrophic respiration (R a ), heterotrophic respiration (R h ), and net ecosystem exchange to variation in RZSM. Gross primary productivity exhibited the largest sensitivity (6.6 ± 10.7 kg·cm −2 ·year·θ −1 ) followed by R a (2.9 ± 7.3 kg·cm −2 ·year −1 ·θ −1 ), R h (2.6 ± 3.1 kg·cm −2 ·year −1 ·θ −1 ), and net ecosystem exchange (−1.7 ± 7.8 kg·cm −2 ·year −1 ·θ −1 ). Analysis shows that these carbon flux sensitivities varied considerably across regions, reflecting influences of canopy structure, soil properties, and the ecophysiological properties of different plant functional types. This study highlights (1) the importance of improved terrestrial biosphere model predictions of RZSM to improve predictions of terrestrial carbon fluxes, (2) a need for improved pedotransfer functions, and (3) improved understanding of how soil characteristics, climate, and vegetation composition interact to govern the responses of different ecosystems to changing hydrological conditions.

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Data-model comparison of temporal variability in long-term time series of large-scale soil moisture

Cited by 10 publications

References 66 publications

Large‐scale comparison of flow‐variability dampening by lakes and wetlands in the landscape

Large‐scale comparison of flow‐variability dampening by lakes and wetlands in the landscape

Large-scale biospheric drought response intensifies linearly with drought duration in arid regions

The Sensitivity of North American Terrestrial Carbon Fluxes to Spatial and Temporal Variation in Soil Moisture: An Analysis Using Radar‐Derived Estimates of Root‐Zone Soil Moisture

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