Forcing, intermittency, and land surface hydrologic partitioning

Marani, Marco; Grossi, Giovanna; Napolitano, Francesco; Wallace, Michael; Entekhabi, Dara

doi:10.1029/96wr02670

Cited by 24 publications

(16 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Changes in the intermittent temporal distribution of meteorological variables are recognized to have nonlinear effects on hydrological processes such as evaporation and infiltration (11), requiring that high-frequency variability of meteorological drivers be accurately represented in hydrological models (12). It is understood that ecosystems also respond nonlinearly to environmental variation (13), but there has been little investigation into the effects of high-frequency variability on the terrestrial biosphere.…”

mentioning

confidence: 99%

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

Medvigy¹,

Wofsy

Munger

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

108

View full text Add to dashboard Cite

We assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.carbon fluxes | climate variability | climate-ecosystem models | terrestrial biosphere | Harvard Forest

show abstract

mentioning

confidence: 99%

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

Medvigy¹,

Wofsy

Munger

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

108

View full text Add to dashboard Cite

show abstract

“…Table I lists the soil hydraulic parameters at the twenty sampling locations. The thickness of the vadose zone was determined by a spatial and temporal average of groundwater table depths observed over a 7-year period at the sampling locations (Water Resources Bureau, 1991-1997.…”

Section: Description Of the Study Areamentioning

confidence: 99%

“…For example, Kim et al (1996) used the Brooks and Corey (1964) soil-water characteristics model coupled with Richards' equation to formulate a simplified, transient water budget model that describes evapotranspiration as a sink term withdrawing water from the entire soil profile. Marani et al (1997) used a statistical-dynamic model to investigate the effects of intermittency (i.e., intensity and duration) of storms, soil type, and water table depth on the partitioning of rainfall into runoff, evaporation, and recharge. They concluded that the temporal structure of storms has a strong influence on the long-term equilibrium state of the hydrological system.…”

Section: Introductionmentioning

confidence: 99%

A Water Budget Model for the Yun-Lin Plain, Taiwan

Chen

Lee

Yeh

et al. 2005

Water Resour Manage

View full text Add to dashboard Cite

A water budget model is proposed to estimate the infiltration, runoff, evapotranspiration and recharge in vadose zone and apply to a case study. The instantaneous redistribution of infiltrated water is assumed to be uniform and a linear relationship between evapotranspiration and effective saturation is imposed. Infiltration is described by Philip's solution in conjunction with the time compression approximation method during rainfall. Runoff occurred when rainfall rate exceeds soil-infiltrating rate. The soil profile drainage was determined by evapotranspiration and recharge. Cumulative infiltration, runoff, evapotranspiration and recharge are estimated with different climate conditions and different soil hydraulic properties during simulating period. Analysis shows that initial effective saturation affects the estimated results in this water budget model in the short or mid-term simulations while not in long-term simulations. The climatic conditions of Yun-Lin plain area, Taiwan from 1991 to 1997 are used by referring to hydrological and hydrogeological parameters to provide the computational procedures of this study for estimating recharge. Results showed that the amount of annual recharge was affected by the amount of annual rainfall and soil properties. Nomenclature A = Parameter related to sorptivity [L 1/2 ] a = Infiltration constant [−] D = Diffusivity [L 2 T] d r = Depth of water reservoir [L] E = Evapotranspiration flux [L T −1 ] E p = Potential evapotranspiration rate [L T −1 ] i = Infiltration rate [L T −1 ] k = Unsaturated hydraulic conductivity [L T −1 ] k s = Saturated hydraulic conductivity [L T −1 ] P = Rainfall intensity [L T −1 ] P cum (t) = Cumulative rainfall [L] S = Sorptivity [L T −1/2 ] t = time [T] t e = Equivalent time to ponding [T] t p = Ponding time [T] 484 J.-F. CHEN ET AL. q = Unsaturated water flux [L T −1 ] q cum ie (t) = Amount of infiltration excess runoff [L T −1 ] q cum se (t) = Amount of saturation excess runoff [L T −1 ] q r = Recharge flux [L T −1 ] φ = Effective saturation [−] φ 0 = Initial effective saturation [−] λ = Pore size distribution index [−] θ = Volumetric water content [−] θ 0 = Initial volumetric water content [−] θ r = Residual water content [−] θ s = Saturated water content [−] h = Soil pressure head (<0 if soil unsaturated) [L] h s = Air entry value [L] h 0 = Initial soil pressure head [L]

show abstract

“…However, as shown above, due to the randomness in the RPM model, each realisation will have a unique sequence of storms that will cause differences between the actual rainfall sequence and the disaggregated realisations. The importance of the intermittent temporal structure of precipitation forcing on hydrological partitioning at the land surface has been shown in Marani et al (1997). Thus, if the techniques discussed above are to be used to produce forcing time series for hydrological applications, it is important to investigate the effect of differing intermittent temporal structure in the precipitation forcing at the land surface.…”

Section: Propagation Of Error In Land Surface Modelsmentioning

confidence: 99%

“…involved in a storm sequence. Marani et al (1997) describe the important effects of the intermittent temporal structure of precipitation forcing on hydrological partitioning at the land surface. Their results show that due to the threshold and nonlinear dependencies of surface hydrological processes on precipitation, the hydrological response of the surface can vary considerably based on the intermittent temporal structure of the forcing.…”

Section: Introductionmentioning

confidence: 99%

Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

Margulis

Entekhabi

2001

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc.), it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error.

show abstract

Forcing, intermittency, and land surface hydrologic partitioning

Cited by 24 publications

References 17 publications

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

A Water Budget Model for the Yun-Lin Plain, Taiwan

Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

Contact Info

Product

Resources

About