Characteristics of canopy interception and its simulation with a revised Gash model for a larch plantation in the Liupan Mountains,China

Zebin Liu·Yanhui Wang·Ao Tian·Yu Liu·Ashley A.Webb·Yarui Wang·Haijun Zuo·Pengtao Yu·Wei Xiong·Lihong Xu

Introduction

Forests provide hydrological regulation services which involve the partitioning of rainfall into interception,throughfall and stem flow as it falls through the forest canopy.These are very important forest hydrological processes(Marin et al.2000;Ahmadi et al.2009).Canopy interception will affect the amount of available soil water and thus also the growth(Fang et al.2013).The annual canopy interception ratio is in fluenced by many factors(such as stand type,tree density,canopy structure and rainfall characteristics),and differs signi ficantly,with a general range of 10–48%,or even above 50%in some instances(Zhang et al.2006;Hörmann et al.1996;Chang et al.2006).Throughfall is the main rainwater input to the forest floor,and has a crucial in fluence on a series of hydrological processes such as soil in filtration,surface runoff,inter flow,soil water changes,evaporation and transpiration.Throughfall is affected firstly by meteorological conditions(i.e.rainfall depth and intensity),and then by tree growth characteristics(i.e.leaf area index(LAI),canopy thickness,branch shape and leaf angle);and generally accounts for 72–97% of the gross rainfall(Chuyong et al.2004;Holwerda et al.2006;Vernimmen et al.2007).Although stem flow accounts for a very small proportion of rainfall,it can concentrate water and nutrients into a small area around tree trunks with profound impacts on the hydrological and ecological performances(Chang and Matzner 2000;Li et al.2009;Germer et al.2010,2012).Stem flow varies greatly and is affected by a number of tree growth factors(stand density,trunk diameter,the angle of trunk and branches,the roughness and water-absorbing capacity of the bark)and meteorological conditions(Levia and Frost 2003;Limousin et al.2008;Van Stan et al.2016).

Canopy interception models are important tools for understanding,describing,estimating,and predicting forest interception.At present,numerous models have been developed,includingempiricalones(linear,logarithmicand exponential function),semi-empirical ones(Rutter,Gash,and Calder)and theoretical models(Rutter et al.1971;Calder1986;Gashetal.1995;Liu1988).However,manyof thesearenotwidelyusedduetotheirdifferentemphasesand lack of universality.Muzylo et al.(2009)compared the applicability of 15 main canopy interception models with field data and found the most commonly applied ones were the original and revised Gash models.In recent years,the revised Gash model has been well applied in many coniferous and broad-leaf forests in China,such as the forests of Phyllostachys edulis(Carrière)J.Houz.(Zhao et al.2011),Pinus armandii Franch.(Shi et al.2010)and Quercus aquifolioides Rehder and E.H.Wilson(He et al.2010).However,no study has reported application of the revised Gash model to plantations of Larix principis-rupprechtii(larch),one of the main afforestation species for both timber production and environmental restoration in the wide expanses of north,northeast and northwest China.If the revised Gash model can successfully simulate canopy interceptionbylarchplantations,itwillbeavaluabletoolfor the prediction and evaluation of hydrological impacts,soil erosion control and many other related ecosystem services,as well as for multi-functional forest management.

The objectives of this study are:(1)to quantify the partition of gross precipitation into interceptloss,throughfall,and stem flow based on field measurement;(2)to determine the values of the meteorological and vegetation parameters required in the revised Gash model;(3)to evaluate the performance of the revised Gash model;and(4)to compare the effects of meteorological and vegetation parameters on canopy interception.

Materials and methods

Study site

The study site is the small watershed of Xiangshuihe(106°09′–106°30′E,35°15′–35°41′N) located in the southern part of the National Natural Reserve of the Liupan Mountains in northwest China(Fig.1).The watershed has an area of 43.7 km2,altitudes of 2010–2942 m a.s.l.,a temperate semi-humid climate with a mean annual temperature of 6.0°C and mean annual precipitation of 632 mm.The vegetation is dominated by natural secondary forests of P.armandii,Quercus liaotungensis Koidz.,Betula platyphylla Sukaczev and Betula albo-sinensis Burk.,with an area of 25.3 km2.The plantation area amounts to 10.4 km2and is mainly composed of Larix principisrupprechtii with a small proportion of Pinus tabulaeformis Carr.

Within the watershed,a pure larch plot with an area of 900 m2(30 m×30 m)was located on a southeast-facing slopewithameangradientof21°andanelevationof2410 m.This plot had a canopy density of 0.73,a tree density of 833 stems ha-1,an age of 34 years,a mean tree height of 18.15±2.03 m,a mean DBH of 20.71±3.91 cm,a mean clean height of 5.30±0.67 m,and a mean canopy diameter of 4.67±0.79 m.

Measurements of gross rainfall and its partitions

During the 2015 growing season(May 6 to October 31),gross rainfall was measured with two rain gauges with sectional areas of 230.58 cm2(18.3 cm×12.6 cm),and calibrated with the simultaneously recorded duration and intensity of rainfall by an automatic weather station(Weatherhawk 232,Weatherhawk Inc.,Logan,Utah,USA)located in an open area about 100 m away from the experimental plot.At the same time,air temperatures,relative air humidities,solar radiation intensities and wind speeds were recorded every 5 min.

Throughfall was collected and measured after each rainfall event using rain gauges of the same size as those for measuring gross rainfall.Forty(40)rain gauges were evenly distributed within the plot at fixed positions.The average of the measured throughfall volume(ml)in rain gauges was converted into throughfall depth(mm).

Fig.1 Study site and location of plantation plot

The trees were divided into four DBH classes(＜16 cm,16–20 cm,20–24 cm,＞24 cm).Two sample trees from each DBH class were selected for collecting the stem flow of each rainfall event through halved plastic tubes stapled on the trunks in a spiral and sealed with silicone to direct the stem flow into a water cylinder.The measured stem flow volume(ml)was converted into stem flow depth(mm)using the following equation:

where SF is the stem flow depth(mm),N the number of DBH classes(N=4 in this study).Cithe average stem flow volume(ml)from sample trees in DBH class i,Mithe number of trees belonging to DBH class i on the plot,and Spthe area of the study plot(m2).

Canopy interception was determined indirectly through the water balance of the canopy(Iida et al.2005)using the equation below:

where I is the canopy interception(mm),PGthe gross rainfall(mm),TF the throughfall(mm).

The revised Gash model

The revised Gash model(Gash et al.1995;Limousin et al.2008)describes the total canopy interception of a series of independent rainfall events.The model divides each event into three sequential phases:wetting phasesaturation phase,and drying phase after rain has ceased(from the cessation of rainfall to the time when the canopy and trunks have dried);whereis the rainfall outside of the forest for the rainfall event j;andis the rainfall amount necessary to saturate the canopy.The model assumes no canopy drip before the canopy becomes saturated;stem flow occurs after the canopy reaches saturation;evaporation from the trunk only occurs after the rain has ceased;and that there is suf ficient time to dry the canopy between two adjacent rainfall storms.The model divides the forested land into two parts:an area with canopy and area without.The canopy-covered area equals the product of forest area and canopy density(c).It further assumes that there is no evaporation of intercepted rainfall in the area without canopy;thus the mean evaporation of the whole forest area may be expressed as the evaporation from the canopy-covered area.Similarly,the structure parameters of the canopy(covered area)may be calculated based on all the forested land parameters and canopy density(c).For example,canopy interception capacity(Sc),trunk capacity(Stc)and stem flow(Ptc)of the canopy(covered area)may be calculated by using the corresponding means of the whole forest(S,St,and Pt)and the canopy density(c).

The rainfall quantity required to saturate the canopy is calculated using:(Gash et al.1995):

The rainfall quantity necessary to saturate the trunks is calculated using:(Valente et al.1997):

The basic formula of the revised Gash model to calculate total canopy interception of a series of rainfall events during a certain period is described as following(Limousin et al.2008):

where Ijis the canopy interception of rainfall event j;n+m the number of rainfall events;n the number of rainfall events which saturate the canopy;m the number of rainfall events which cannot saturate the canopy;the mean rainfall intensity(mm/h);the mean evaporation rate from the canopy area when the canopy is saturated during rainfallE the mean evaporation rate for the forested area when the canopy is saturated during rainfall;q the number of rainfall events which can fill the trunk storage capacity so that stem flow may appear.is the interception for small rainfall events which are insuf ficient to saturate the canopy;the interception for rainfall events which can saturate the canopy;the evaporation from the canopy for n rainfall events until rainfall ceases;qcStcthe evaporation from trunks for q rainfall events which saturate the trunks;the evaporation from trunks for n–q rainfall events which are insuf ficient to saturate the trunks.

The mean evaporation rate for the forested area when the canopy is saturatedis calculated using the Penman–Monteith equation:

where λ is the latent heat of vaporization of water(20 °C,2453.6 J/g);Δ the slope of the curve relating saturated vapor pressure to temperature(hpa/°C), Δ =40980ET/(237.3+ θ)2;(ETis saturation vapour pressure,hpa;θ the air temperature,°C);Rnthe net radiation(W/m2);ρ the air density(20°C,1016.5 g/m3);cpthe speci fic heat of air(1.0048 J/(g°C));D the saturation pressure de ficit,D=ET-eT(eTthe actual vapor pressure,hpa);γ the psychometric constant(0.664 hpa/°C);and rathe aerodynamics resistance(s/m).

Saturation vapour pressure and actual vapor pressure are calculated by using the following equations:

where RH is the relative air humidity(%).

Aerodynamic conductance(ra)is calculated as follows:

where k is von Karman’s constant(k=0.41);μ (m/s)the wind speed at height z(m);z the reference height above the ground(z=h+2 m,where h is the average tree height),d the zero plane displacement height;and z0the roughness length for momentum.Following Monteith and Unsworth(1990),d and z0were taken as0.7 h and 0.1 h,respectively.

According to the following equations,throughfall and stem flow may be estimated by the revised Gash model(Limousin et al.2008):

Results

Characteristics and partitioning pattern of rainfall

During the study period,a total of 34 rainfall events were observed.There were three which presented a higher measuredvalueofthroughfallthanthegrossrainfall,leadingtoa negativecalculatedcanopyinterception.Thedatafromthese three were excluded(Tian et al.2012),meaning only the remaining data from 31 events were used.The rainfall amount of the 31 events varied from 1.0 to 69.0 mm,with a total of 499.0 mm and an average of 16.1 mm.The duration of individual rainfall events varied from 0.5 to 48.0 h,with anaverageof10.0 hperevent.Intensitiesvariedfrom0.38to 8.66 mm/h,with an average of 2.51 mm/h.

The cumulative throughfall of the 31 events was 410.3 mm,accounting for 82.2%of the contemporaneous total rainfall.Throughfall per event varied from 0 to 8.0 mm,with an averageof13.2 mm.Throughfall increased with rising gross rainfall(Fig.2a),with a signi ficant linear correlation as follows:

Of the 31 rainfall events,23 produced an amount more than 5 mm and so could generate stem flow.The cumulative stem flow was 2.0 mm,accounting for only 0.41%of contemporaneous total rainfall.The stem flow of single rainfall events varied from 0 to 0.5 mm,with an average of 0.1 mm.With rising gross rainfall,stem flow increased following a piecewise linear relation(Fig.2b)below:

Corresponding to the 31 events,the total interception loss was86.7 mm,accountingfor17.4%ofthecontemporaneous total rainfall.The interception ratio for incident rainfall events varied from 0.8 to 97.9%.For smaller events(PG-≤6 mm),the mean interception ratio was 81.1%,but it decreased sharply with rising gross rainfall and gradually stabilized after the gross rainfall was more than 20 mm(Fig.3).This relationship may be expressed as an exponential decay function:

Determination of model parameters

Fig.2 Variation of throughfall and stem flow with rainfall depth of individual rainfall events

Fig.3 Variation of canopy interception rate with rainfall amount of individual events

In this study,canopy storage capacity was determined according to Wallace and McJannet(2006),and is the negative intercept of the linear relationship of under-forest rainfall(sum of throughfall and stem flow)against gross rainfall.According to the linear regression equation:(TF+SF)=0.992PG-2.6673(R2=0.9940,n=31),the canopy storage capacity of the larch plantation(S)was 2.67 mm.Since the canopy density(c)was 0.73,canopy storage capacity of the pure canopy,i.e.for the canopy covered area of the plantation,was Sc=S/c with a value of 3.66 mm.Stem flow ratio to rainfall(Pt)and trunk storage capacity(St),which equaled the slope and negative intercept of the linear regression equation of stem flow against gross rainfall(SF=0.0074PG-0.0662,R2=0.9538,n=23),was 0.0074 and 0.0662 mm,respectively.The mean evaporation rate of the saturated canopy for the entire plantation during rainfall(E),as derived from the Penman–Monteith equation(Eq.6),was 0.049 mm/h.Correspondingly,the mean evaporation rate of saturated canopy for the canopy covered plantation during rainfallwas 0.067 mm/h.The amount of rain required to saturate the canopy,as derived from Eq.3,was 3.70 mm.The values of relevant parameters used in the revised Gash model are listed in Table 1.

Comparison of simulated and measured canopy interception

The simulated values of total interception,stem flow and throughfall during the monitoring period,based on the revised Gash model and the parameters of the study plot are listed in Table 1,with the values of 84.5,1.7 and 412.8 mm,respectively.The revised Gash model underestimated the interception and stem flow by 2.2 and 0.3 mm,respectively,with a relative error of 2.5 and 15.0%compared with the observed values;it overestimated the throughfall by 2.5 mm with a relative error of 0.6%.Table 2 shows the components of interception simulated by the model.The interception as evaporation after rainfall ceased(Ia)accounted for 79.0%;the intercepton for small rainfalls which were insuf ficient to saturate the canopy(Ic)accounted for 9.5%;the interception as evaporation from canopy saturation until rainfall ceased(Is)accounted for 9.1%;the interception as evaporation from trunks(It)accounted for 1.4%;and the interception for wetting-up the canopy in saturation events(Iw)accounted for 1.0%.

Figure 4a shows a comparison between measured and simulated canopy interception of single rainfall events,indicating that the overall trend coincided with the actual situation,especially during rainfall events after the complete canopy development.However,most of the simulated values in the mid-and early stages of the growing season were lower than the observed values,and the maximum difference was 2.2 mm,indicating that there was a structural de ficiency in the revised Gash model for the simulation of canopy interception.Unlike the simulated results of canopy interception of single rainfall events,the simulated throughfall and stem flow of single rainfall events were close to the observed results during the whole growing season(Fig.4b,c).

Parameters sensitivity

In order to determine the effects of the model parameters on the simulation value of total canopy interception for the larch plantation,a sensitivity analysis for the atmospheric variablesand canopy structure parameters(S,c,Ptand St)was conducted(Fig.5).The simulated value of canopy interception showed the highest sensitivity for the changes of S.If the values of S increased by 20%,it would rise by 15%.The simulated value of canopy interception was also highly sensitive to the changes of c and R.If the values of c or R increased by 20%,it would rise by 3.6%or decrease by 3.2%.In contrast,canopy interception was insensitive to E,Stand Pt,indicating that these parameters have a small effect on the interception loss.

Table 1 Parameters in the revised Gash model used to simulate interception

Table 2 Components of simulated interception

Fig.4 Comparison of measured and simulated canopy interception,throughfall and stem flow of single rainfall events

Fig.5 Analysis of sensitivity of parameters in the revised Gash model

Discussion

The interception ratio of the L.principis-rupprechtii plantation was 17.4%,within the range of 14.7–31.8%reported for the major forest types in China(Wei et al.2005)but lower than magnitudes reported for L.principisrupprechtii elsewhere(Table 3),such as the 22.9%in Heibei Province reported by Liu et al.(2011),and the 23.2%in Qinghai Province reported by Lu et al.(2014).However,the throughfall ratio in this study(82.2%)was higher than in these other two studies(Table 3).Canopy interception and throughfall were in fluenced by a number of factors.In addition to stand structure,such as leaf area index,canopy density and stand density(Deguchi et al.2006;Gómez et al.2002;Bryant et al.2005),the amount of rainfall can also affect canopy interception and throughfall.In our study,the canopy density was lower than in the other two studies,while rainfall was higher which might be reasons for the lower interception ratio and higher throughfall ratio in our study.

The stem flow ratio of forests is low for most species,only accounting for 0.018–13.9%of gross rainfall,and even less than 2%for conifer species(Tian et al.2012;Marin et al.2000;Carlyle-Moses 2004).However,the collection of water and nutrients brought by stem flow to the stem bases could help absorption by tree roots(Crockford and Richardson 2000;Levia and Herwitz 2005),and therefore there is of signi ficance for tree growth.Affected by rainfall characteristics,stand density,stand age,the thickness of trunk,the angle of trunk,roughness and water absorbing capacity of bark,the stem flow ratio may be different even within the same species(Limousin et al.2008;Crockford and Richardson 2000;Livesley et al.2014;Van Stan et al.2016).In our study,the stem flow ratio of the L.principis-rupprechtii plantation was 0.4%,between studies of stem flow for the same species in other areas(Table 3).

In our study,most of the predicted interception can be explained by Ia,accounting for 79.0%of the total simulated interception,which is consistent with the results of a P.armandii forest in the same area reported by Shi et al.(2010).It differs from the findings of several researchers who found Iswas the main part of the simulated interception(Chen et al.2013;Su et al.2016).The reasons for this difference might be related to a higher canopy storage capacity of L.principis-rupprechtii and lower evaporation rate during the rainfall event in our study due to higher altitude,higher humidity and lower temperature.

The simulated interception by the larch plantation for the whole growing season is in agreement with the observed value.The simulated value was only 2.2 mm lower than the observed value,with a relative error of 2.5%.Muzylo et al.(2009)classi fied the relative error into 5 levels to evaluate the performance of interception models:extremely good(error≤1%of observed interception);very good(1%＜error≤5%);good(5%＜error≤10%);fair (10%＜error≤ 30%); and bad (error＞30%).According to this,the performance of the revised Gash model for the larch plantation in our study was ‘very good’.The model tended to underestimate interception in most previous studies,especially the individual rainfall events as large storms or discrete rainfall events(Limousin et al.2008;Shi et al.2010;Motahari et al.2013).The prediction errors of throughfall and stem flow for the whole growing season were 0.6 and 15.0%,respectively,indicating that the revised Gash model can work well for estimating total throughfall and stem flow.Similar results were reported formixed evergreen and deciduousbroadleaved forests(Su et al.2016)and primary Korean pine(Pinus koraiensis Sieb.)forest(Chai et al.2013).

Table 3 Comparison of canopy interception and stem flow among different sites

In our study,the simulated throughfall and stem flow for individualrainfallevents were coincidentwith the observed values,indicating that the revised Gash model can also perform well for the simulation of throughfall and stem flow during single rainfall events.The overall trend of the simulated interception for individual rainfall events was consistent with that of observed interception.The simulated results were good,especially after the complete development of the canopy,i.e.,during the middle and late growing seasons.However,the simulated results were poor for several rainfall events during the early and middle growing seasons,which might be related to the fact that the hypothetical conditions were different from the actual situation(Chai et al.2013).For example,the model assumes that the canopy is full of needles and opaque within the canopy projection area,while there would be more and larger pores in the canopy of the larch forest when the leaves were not fully expanded during the early spring.Drought could lead to higher evaporation during the early and middle growing season(Nassar 1979)but the use of average evaporation rate for the whole growing season will make the model underestimate the canopy interception;the rainfall might be intermittent and low intensity during the early and middle growing season,while the model was unable to distinguish the rainfall intensity among independent rainfall events.For rainfall events which are composed of several short rainfall-free intervals,the model will underestimate the canopy interception due to the ignorance of the recovery of interception ability of the canopy by evaporation during rainfall-free intervals(Wang et al.2012).Furthermore,canopy interception ability varies during the growing season,especially for deciduous forests with very obvious seasonal differences,while the model assumes fixed canopy interception ability.Therefore,the model structure could be improved further to improve the precision of simulations,for example,by establishing the relationship between canopy interception capacity and leaf area index and attempting to use dynamic interception ability instead of static interception capacity.Further improvements could consider the degree of wetting of the canopy and bark before rainfall events and replacing the constant interception capacity with the varying effective interception capacity;determine the model parameters by statistical fitting of observed data instead of the current analytical approach;and improve the classi fication of independent rainfall events.

To a great extent,the precision of canopy interception simulation of the revised Gash model depends on the accuracy of the estimated model parameters.In our study,canopy storage capacity(S)was the most in fluential parameter for the precision of canopy interception.This is consistent with the results with Pinus pinaster Aiton(Gash et al.1995),Pinus tabulaeformis(Fang et al.2013)and Quercus aquifolioides(He et al.2010),indicating the accurate estimation of canopy storage capacity was key to improving the simulation accuracy.

At present,there are several methods to estimate canopy storagecapacity,suchastheregressionmethod(Leytonetal.1967;Wallace and McJannet 2006;Pereira et al.2009),the scalepushingmethod(LlorensandGallart2000;Marinetal.2000)and the remote sensing method(Bouten et al.1991;Calder and Wright 1986).Each method has its advantages.The canopy storage capacity of L.principis-rupprechtii determined through the regression method by Wallace and McJannet(2006)was 2.67 mm,higher than the reported values of several other coniferous forests(Chen et al.2013;Fang et al.2013;Motahari et al.2013;Návar 2013)but within the reported scope of canopy storage capacity of coniferous forests of 0.3–3 mm based on the analysis of literature from 1968 to 2000 by Llorens and Gallart(2000).In addition,several studies reported similar canopy storage capacitiesforconiferousforestsinrecentyears,forexample,2.68 mm with Pinus tabuliformis(Liang and Ding 2013),2.86 mm for P.armandii(Shi et al.2010),3.3 mm for Abies fabri(Mast.)Craib(Link et al.2004)and 4.70 mm with Cunninghamialanceolata(Lamb.)Hook(Liuetal.2015).In addition to bark morphology,the shape and dimension of leaves,the orientation of branches(Návar and Bryan 1990;Motahari et al.2013),the leaf area index(LAI)may also affect canopy storage capacity(Llorens and Gallart 2000;Fleischbein et al.2005).High canopy storage capacity tends to be accompanied by high LAI(Liu 1998).The value for canopy storage capacity relative to LAI in our study was reasonable compared to the values determined for other conifer canopies(Fig.6),indicating that the evaluation accuracy of canopy storage capacity in this study was acceptable.

Fig.6 Canopy storage capacity and corresponding leaf area indices in different studies

This study also showed that canopy density(c)and average rainfall intensity(R)are important factors in fluencing the simulation accuracy for canopy interception of the larch plantation.This is in accordance with the results of canopy interception by Quercus ilex L.stands in the Mediterranean(Limousin et al.2008),and by P.edulis stands in the Jinyun Mountains(Zhao et al.2011),and by Picea crassifolia stands in Qinghai(Gao et al.2015).In addition,the average evaporation rate,trunk storage capacity(St)and the proportion of rainfall diverted to stem flow(Pt)had little in fluence on the simulation accuracy of canopy interception by the larch plantation.The reason may be that stem flow only accounts for a small percentage of the gross rainfall,and the change of Stand Ptwill not have a great in fluence on the simulated canopy interception.This result is consistent with the results of other studies(Limousin et al.2008;Shi et al.2010;Mu˙zyło et al.2012).The average evaporation rate during our study was 0.049 mm/h,lower than the average evaporation rate in most other studies(Wallace and Mcjannet 2008;Návar 2013).This was mainly attributed to the cold weather and highly saturated vapor pressure at the study site(Shi et al.2010).Several studies have shown that the average evaporation rate is a highly sensitive climate parameter for the simulation of interception(Deguchi et al.2006;Fang et al.2013).The change of average evaporation rate had little in fluence on the simulated interception in our study and can be largely attributed to the much lower average evaporation rate.

Conclusions

Canopy interception of rainfall by a larch plantation during the growing season may be summarized as:

1. Total throughfall,stem flow and interception were 410.3,2.0 and 86.7 mm,accounting for 82.2,0.4 and 17.4%of the total rainfall,respectively.During the study period,the average rainfallintensity was 2.51 mm/h;the average evaporation rate during rainfall events 0.049 mm/h;canopy and trunk storage capacity 2.67 and 0.066 mm,respectively;and the proportion of rainfall diverted to stem flow 0.007.

2. The parameters of the revised Gash model were determined based on observed data in the larch plantation.The estimated total interception during the growing season was 84.5 mm,only 2.2 mm lower than the observed value,with a relative error of 2.5%;the estimated total throughfall was 412.8 mm and only 2.5 mm higher than the observed value,with a relative error of 0.6%;the estimated total stem flow was 1.7 mm,only 0.3 mm lower than the observed value,with a relative error of 15.0%.The revised Gash model can well simulate total canopy interception and stem flow,and the canopy interception of most individual rainfall events.Therefore,the revised Gash model with the fitted parameters in this study has a good applicability for estimating canopy interception in L.principis-rupprechtii plantations.

3. However,the simulated values for some individual rainfall events do not correspond well with the measured values,indicating the revised Gash model has structural defects for the simulation of individual rainfall events.For example,the model cannot re flect and consider the dynamic interception capacity,wet canopy evapotranspiration rate,or the canopy wetting degree before rainfall.In addition,the model structure and the determination method of model parameters should be further re fined to improve the simulation precision and model applicability.

AcknowledgementsThis research was funded by the National Key Research and Development Program of China(2016YFC0501603),the National Natural Science Foundation of China(Nos.41671025;41390461;41230852;41471029).We also thank the Key Laboratory of Forest Ecology and Environment of State Forestry Ministry for support.

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