Monitoring and modelling canopy water storage amounts in support of atmospheric deposition studies

Bouten, W.; Schaap, M. G.; Aerts, J.C.J.H.; Vermetten, A.W.M.

doi:10.1016/0022-1694(95)02907-9

Cited by 58 publications

(27 citation statements)

References 14 publications

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“…These include the strain-gauge measurement of cantilever¯exing of branches under the load of intercepted water (Hancock and Crowther, 1979) and the attenuation of a microwave signal by water held on plant canopies lying in its path (e.g. Bouten et al, 1991Bouten et al, , 1996Wigneron et al, 1996).…”

Section: Discussionmentioning

confidence: 99%

Measuring interception loss and canopy storage in dryland vegetation: a brief review and evaluation of available research strategies

2000

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Abstract:The interception storage capacity has been measured for a range of dryland plants. Interception losses over time, however, arise in rain events that deliver either less or more than the canopy capacity. The fate of water in these cases depends on the eciency with which the intercepted water is returned to the atmosphere by evaporation from the plant canopies. Two primary methods to estimate interception losses are (i) calibrated process-based models of interception and evaporative loss and (ii) direct measurement. Models have been applied only rarely to dryland plant communities, and direct measurement techniques are in need of additional testing and re®nement. Most published estimates of interception loss in dryland plant communities therefore appear to be based upon inadequate data and methods. Research needs in this area are highlighted.

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Section: Discussionmentioning

confidence: 99%

Measuring interception loss and canopy storage in dryland vegetation: a brief review and evaluation of available research strategies

2000

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“…Bouten et al, 1996). The difference between observed and predicted values of was lower than in previous applications of the Gash model in similar climatic conditions (Lankreijer et al, 1999).…”

Section: Rainfall Interceptionmentioning

confidence: 67%

“…During the 1990's research focused on the impact of air pollution on forest growth ('Aciforn project') at this site (Evers et al, 1991a). Several hydrological studies at that time found high interception losses (~40 %) from the forest (Tiktak and Bouten, 1994;Klaassen et al, 1998;Bouten et al, 1996), contributing to the debate about forest plantations in the centre of the Netherlands affecting the ground water recharge (Moors, 2012).…”

mentioning

confidence: 99%

“…Detailed measurements and modelling studies at the site included canopy growth and architecture (Evers et al, 1991b), soil 15 water dynamics (Tiktak and Bouten, 1994), modelling evaporation and transpiration (Bosveld and Bouten, 2001), spatial patterns of throughfall (Bouten et al, 1992), and measuring and modelling canopy water storage (Bouten et al, 1991;Bouten et al, 1996). It was found that the high interception losses in Speulderbos at that time were due to a high leaf area index, resulting in high canopy storage capacity (2.5 mm) as measured by microwave transmission (Bouten et al, 1991).…”

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confidence: 99%

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The influence of long-term changes in canopy structure on rainfall interception loss: a case study in Speulderbos, the Netherlands

Vaca¹,

Tol²,

Ghimire³

2018

Preprint

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Abstract. The evaporation of intercepted water by forests is a significant contributor to both the water and energy budget of the Earth. In many studies, a discrepancy in the water and energy budget is found: the energy that is needed for evaporation is larger than the available energy supplied by net radiation. In this study, we analyse the water and energy budget of a mature 10 Douglas-fir stand in the Netherlands, for the two growing seasons of 2015 and 2016. Based on the wet-canopy water balance equation for these two growing seasons, derived interception losses were estimated to be 37% and 39% of gross rainfall, respectively.We further scrutinized eddy covariance energy balance data from these two consecutive growing seasons and found the average evaporation rate during wet canopy conditions was 0.20 mm h -1 . The source of energy for this wet-canopy evaporation was 15 net radiation (35 %), a negative sensible heat flux (45 %) and a negative energy storage change (15 %). This confirms that the energy for wet-canopy evaporation is extracted from the biomass as well as the atmosphere.Moreover, the measured interception loss at the forest was similar to that measured at the same site years before ( = 38 %), when the forest was younger (29 years old, vs 55 years old in 2015). At that time, the forest was denser and had a higher canopy storage capacity (2.4 mm then vs 1.90 mm in 2015), but the aerodynamic conductance was lower (0.065 m s -1 then vs 20 0.105 m s -1 in 2015), and therefore past evaporation rates were lower than evaporation rates found in the present study (0.077 mm h -1 vs 0.20 mm h -1 in 2015). Our findings emphasize the importance of quantifying downward sensible heat flux and heat release from canopy biomass in tall forest in order to improve the quantification of evaporative fluxes in wet canopies.

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“…Grings et al (2009) have used radar remote sensing to explore the water storage of wetlands of the Paraná River Delta in Argentina. However, the remote sensing techniques and other relative techniques based on gamma-ray (Calder and Wright, 1986) and microwave attenuation (Bouten et al, 1996) are expensive to implement (Liu, 1998), although they are capable of monitoring the water level inside marshes on a regional scale (Bach and Mauser, 2003). Bradley (2002) used the MODFLOW to simulate the annual water table dynamics of a flood plain with a large amount of weekly data.…”

mentioning

confidence: 99%

Evolutionary Algorithm for Water Storage Forecasting Response to Climate Change with Small Data Sets: The Wolonghu Wetland, China

Wang

Zheng

et al. 2012

Environmental Engineering Science

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A novel genetic programming (GP) technique, a new method of evolutionary algorithms, was applied to a small data set to predict the water storage of Wolonghu wetland in response to the climate change in the northeastern part of China. Fourteen years (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) of annual water storage and climatic data of the wetland were used for model training and testing. Results of simulations and predictions illustrate a good fit between calculated water storage and observed values (mean absolute percent error = 9.47, r = 0.99). By comparison, a multilayer perceptron method (a popular artificial neural network model) and Grey theory model with the same data set were applied for performance estimation. It was found that GP technique had better performance than the other two methods, in both the simulation step and the predicting phase. The case study confirms that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under the limitation of a small data set.

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Monitoring and modelling canopy water storage amounts in support of atmospheric deposition studies

Cited by 58 publications

References 14 publications

Measuring interception loss and canopy storage in dryland vegetation: a brief review and evaluation of available research strategies

Measuring interception loss and canopy storage in dryland vegetation: a brief review and evaluation of available research strategies

The influence of long-term changes in canopy structure on rainfall interception loss: a case study in Speulderbos, the Netherlands

Evolutionary Algorithm for Water Storage Forecasting Response to Climate Change with Small Data Sets: The Wolonghu Wetland, China

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