Model Of Rainfall Interception Research Articles

Estimating rainfall interception of xerophytic deciduous shrubs by static- and variable-parameter Gash models with stem- and leaf-dominated canopy water storage

The precise modeling of rainfall interception is important to understand the water balance of forest ecosystems, particularly in water-stressed restoration regions. However, xerophytic deciduous shrubs are currently underrepresented in rainfall interception models due to the significant variations in their canopy structures. Therefore, we estimated the rainfall interceptions of four representative deciduous shrubs (Spiraea pubescens, Potentilla fruticose, Hippophae rhamnoides, and Caragana korshinskii) in the semiarid region of northern China using the revised Gash model (RG model) with static parameters and a modified Gash model (MG model) with variable parameters. The results indicate that the MG model outperformed the RG model in studies of S. pubescens and P. fruticose, with regard to the modeling error (6.6%–7.9%), Nash–Sutcliffe model efficiency (0.68–0.86), and the root-mean-square error (0.17–0.71). However, the RG model was better than the MG model for H. rhamnoides and C. korshinskii, with regard to the modeling error (3.6%–6.3%), Nash–Sutcliffe model efficiency (0.82–0.94), and the root-mean-square error (0.17–0.66). The MG model was highly sensitive to changes in the leaf area index, canopy cover, mean evaporation rate, canopy storage capacity, and leaf storage capacity for S. pubescens and P. fruticose. Nevertheless, the RG model demonstrated high sensitivity to changes in the canopy storage capacity and stem storage capacity for H. rhamnoides and C. korshinskii. These indicated that canopy storage capacity has a significant effect on the rainfall interception capabilities of different shrub species, as indicated by both the RG and MG models. This critical indicator was determined by the water storage of stems for H. rhamnoides and C. korshinskii (ranged contribution of 59.5%–81.6%), whereas the water storage of leaves for S. pubescens and P. fruticose (with contributions of 51.3%–80.7%). Therefore, the optimized RG and MG models are recommended for estimating the rainfall interception of xerophytic shrubs with stem-dominated water storage and leaf-dominated water storage, respectively. This study categorizes the applicability of rainfall interception models in terms of important plant traits to precisely assess the water balance of xerophytic deciduous shrub ecosystems. In future studies, leaf configuration and hydrophobicity are highly recommended to be quantified for further improving rainfall interception models.

Mechanistic Analysis and Numerical Simulation of the 2021 Post‐Fire Debris Flow in Xiangjiao Catchment, China

AbstractWildfires are becoming a global natural disaster under climate change. A worthwhile concern is that the rainfall thresholds that trigger debris flows in catchments affected by recent wildfires are much lower than those that trigger debris flows in catchments with similar environments but that have not experienced wildfires. In this study, we investigated a major post‐fire debris flow event in Xiangjiao catchment triggered by heavy rainfall in 2021. Through the combination of field observation, laboratory experiments and several numerical models (rainfall interception, infiltration, erosion and runoff models), the physical mechanistic analysis and numerical simulation of the post‐fire debris flow in Xiangjiao catchment was carried out. Results show that the simulated deposited area, erosion depth, and the occurrence time of debris‐flow initiation correlate well with the actual situation. It is demonstrated that the numerical simulation method used in this study can be used to effectively describe the characteristics of the initial and propagation stages of the post‐fire debris flow generated by runoff and provide important insights and guidance for the prediction and prevention of debris‐flow disasters in catchments affected by wildfire.

Evaluation of the Gash Rainfall Interception Model in Forest Plantations

Evaluation of the Gash Rainfall Interception Model in Forest Plantations

Rainfall interception by common mistletoe (Viscum album L. ssp. album): An additional water loss from infected forests

AbstractMistletoes have a global distribution and are the largest group of parasitic plants living within the canopies of woody plants. In European forests, Viscum album L. ssp. album (common mistletoe) is a common sight and, despite being considered a pest, can play beneficial roles in the ecosystem. However, mistletoe infections are becoming more severe and widespread throughout Europe, including recent reports of large‐scale host tree mortality events. These mortality events are hypothesized to be a result of increased water stresses from severe mistletoe infections in tandem with drought. In this study, we estimate an additional water loss from mistletoe‐infected forests that has not yet been described: interception, or the storage and evaporation of rainfall. Results from rainfall simulations on mistletoes sampled from Gostynin Forest District (central Poland) indicate mistletoes can store 0.16–1.32 mm of rainwater. Inputting this additional water storage capacity from mistletoes into a rainfall interception model suggests that, depending on the severity of the infection, mistletoes could reduce annual rainwater supply beneath the canopy by 2–11%. In forests experiencing water stress from mistletoe infection and climate change, the rainfall interception by mistletoes represents an additional water loss of a magnitude worthy of future investigation.

The performance of the reformulated Gash rainfall interception model in the Hyrcanian temperate forests of northern Iran

• Reformulated Gash Analytical models (RGAM) applied for seven reforestations. • Models need frequent numbers of rainfall to estimate rainfall interception loss. • RGAM is advisable for predicting interception with small numbers of rain storms. • Ecohydrological parameters dramatically differs between studied stands. Modeling rainfall interception ( I ) is fundamental for understanding the forests’ role in ecohydrological processes in local and regional scales. This research examines the Reformulated Gash Analytical Model (RGAM) applicability for estimating I in seven dissimilar plantations ( Acer velutinum , Quercus castaneifolia , Pinus brutia , Picea abies , and Cupressus sempervirens L. var horizontalis ) in the four reforested areas across the Hyrcanian temperate forests, northern Iran. Field measurements were performed from May-2012 to March-2014 for 167 distinct throughfall and gross rainfall observations. According to our results, the effects of inter-species variation on I value was evident, as P. abies might be the most excellent among the five frequently used tree species for planting project in temperate forests if the primary goal of plantation is to decrease erosion and surface runoff as it intercepted and evaporated more rainfall than other species. Our findings showed that in terms of average-based calculation, the mean of free throughfall coefficient ( p ) value in evergreen needle-leaved reforestations (0.47) was lower than those calculated for deciduous broad-leaved reforestations (0.59), and vice versa for the canopy storage capacity ( S ; 1.85 mm vs . 1.36 mm, respectively), and mean of the ratio of evaporation rate to the mean of rainfall intensity during saturated canopy conditions ( E ¯ / R ¯ ; 0.45 vs . 0.38, respectively). The RGAM satisfactorily estimated I for all species (except for A. velutinum stand), because the estimation error of I was lower than 15% and the Nash–Sutcliffe efficiency was equal to or higher than 0.87. In conclusion, using data from a short time study period to derive canopy ecohydrological parameters as well as modeling I by the RGAM is advisable in reforestation areas across the Hyrcanian temperate forests and regions with similar forest and meteorological attributes.

Assessing the Accuracy and Potential for Improvement of the National Land Cover Database’s Tree Canopy Cover Dataset in Urban Areas of the Conterminous United States

The National Land Cover Database (NLCD) provides time-series data characterizing the land surface for the United States, including land cover and tree canopy cover (NLCD-TC). NLCD-TC was first published for 2001, followed by versions for 2011 (released in 2016) and 2011 and 2016 (released in 2019). As the only nationwide tree canopy layer, there is value in assessing NLCD-TC accuracy, given the need for cross-city comparisons of urban forest characteristics. Accuracy assessments have only been conducted for the 2001 data and suggest substantial inaccuracies for that dataset in cities. For the most recent NLCD-TC version, we used various datasets that characterize the built environment, weather, and climate to assess their accuracy in different contexts within 27 cities. Overall, NLCD underestimates tree canopy in urban areas by 9.9% when compared to estimates derived from those high-resolution datasets. Underestimation is greater in higher-density urban areas (13.9%) than in suburban areas (11.0%) and undeveloped areas (6.4%). To evaluate how NLCD-TC error in cities could be reduced, we developed a decision tree model that uses various remotely sensed and built-environment datasets such as building footprints, urban morphology types, NDVI (Normalized Difference Vegetation Index), and surface temperature as explanatory variables. This predictive model removes bias and improves the accuracy of NLCD-TC by about 3%. Finally, we show the potential applications of improved urban tree cover data through the examples of ecosystem accounting in Seattle, WA, and Denver, CO. The outputs of rainfall interception and urban heat mitigation models were highly sensitive to the choice of tree cover input data. Corrected data brought results closer to those from high-resolution model runs in all cases, with some variation by city, model, and ecosystem type. This suggests paths forward for improving the quality of urban environmental models that require tree canopy data as a key model input.

Testing three rainfall interception models and different parameterization methods with data from an open Mediterranean pine forest

Various models have been developed to simulate rainfall interception by vegetation but their formulations and applications rely on a number of assumptions and parameter estimation procedures. The aim of this study is to examine the effect of different model assumptions and parameter derivation approaches on the performance of the Rutter, Gash and Liu interception models. The Rutter model, in contrast to the other two daily models, was applied both on an hourly and on a daily basis. Hourly data from a meteorological station, one automatic and 28 manual throughfall gauges from a semi-arid Pinus brutia forest (Cyprus) for the period between 01/Jul/2016 and 31/May/2020 were used for the analysis. We conducted a sensitivity analysis for the assessment of the model parameters and variables: canopy storage capacity (S), canopy cover fraction (c), the ratio of mean wet evaporation rate to mean wet rainfall rate (Ēc/R̄) and potential evaporation (Eo). Three parameter derivation approaches were tested: the widely used regression method and an automatic model parameterization procedure for optimization of S and c and for optimization of S (with c observed). The parameterized models were run with daily meteorological data and compared with long-term weekly throughfall data (2008–2019). The Gash and Liu models showed low sensitivity to Ēc/R̄. Test runs with different combinations of S, c and Ēc/R̄ revealed strong equifinality. The models showed high performance for both calibration and validation periods with Kling–Gupta Efficiency (KGE) above 0.90. Gash and Liu models with the automatic model parameterization procedures resulted in higher KGEs than with the regression method. The interception losses computed from the long-term application of the three models ranged between 18 and 20%. The models were all capable of capturing the inherently variable interception process. However, a representative time series of throughfall measurements is needed to parameterize the models.

Fitting the revised Gash analytical model of rainfall interception to Mongolian Scots pines in Mu Us Sandy Land, China

A rainfall interception experiment was completed for Pinus sylvestris var. mongolica plots with stand densities ranging from 925 to 2700 plants ha−1 in Mu Us Sandy Land, China from June to September 2013. The revised Gash analytical model was then applied to the canopy interception of the Mongolian Scots pine plantations. During the experimental process, the incident rainfall (P), throughfall (Tf), and stemflow events (Sf) were collected and measured, and meteorological data were simultaneously obtained on site. The Penman-Monteith equation and Gash regression method were used to estimate the evaporation rate (E) from the saturated canopy. The classical revised Gash calculation procedure and Leyton-constraint method were applied to obtain the canopy storage capacity (S). Parameters such as E, S, stemflow partitioning coefficient (pt), and trunk storage capacity (St) were scaled to the canopy cover fraction per unit area: Ec, Sc, ptc, and Stc in the revised Gash analytical model, which was also used in the simulation of the rainall interception (Tf, Sf, and I). The proportions of the measured Tf, Sf, and I accounted for 62.82%, 1.13%, and 36.05% of P, respectively. The ratios of Ec to rainfall intensity (R), Sc, ptc, and Stc were 0.0260 (0.0458), 1.210 mm (2.006 mm), 0.0630, and 0.0486 mm, respectively, during the experimental period. The analytical model with Ec and Sc equal to 0.182 (Penman-Monteith equation) and 1.210 mm (classical revised Gash calculation procedure) accurately simulated the canopy interception of the Mongolian Scots pine plantations, and the canopy interception variation in the analytical model was sensitive to P, Sc, Stc, c, Ec, and R, but was relatively insensitive to ptc.

Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

The interception of rainfall by vegetation canopies plays an important role in the hydrologic process of ecosystems. Most estimates of canopy rainfall interception in present studies are mainly through field observations at the plot region. However, it is difficult, yet important, to map the regional rainfall interception by vegetation canopy at a larger scale, especially in the southern rainy areas of China. To obtain a better understanding of the spatiotemporal variation of vegetation canopy rainfall interception with regard to the basin scale in this region, we extended a rainfall interception model by combining the observed rainfall data and moderate resolution imaging spectroradiometer leaf area index (MODIS_LAI) data to quantitatively estimate the vegetation canopy rainfall interception rate (CRIR) at small/medium basin scales in Guangdong Province, which is undergoing large changes in vegetation cover due to rapid urban expansion in the area. The results showed that the CRIR in Guangdong declined continuously during 2004–2012, but increased slightly in 2016, and the spatial variability of CRIR showed a diminishing yearly trend. The CRIR also exhibited a distinctive spatial pattern, with a higher rate to the east and west of the mountainous areas and a lower rate in the central mountainous and coastal areas. This pattern was more closely related to the spatial variation of the LAI than that of rainfall due to frequent extreme rainfall events saturating vegetation leaves. Further analysis demonstrated that forest coverage, instead of background climate, has a certain impact on the canopy rainfall interception, especially the proportion of broad-leaved forests in the basin, but more in-depth study is warranted in the future. In conclusion, the results of this study provide insights into the spatiotemporal variation of canopy rainfall interception at the basin scale of the Guangdong Province, and suggest that forest cover should be increased by adjusting the species composition to increase the proportion of native broad-leaved species based on the local condition within the basin. In addition, these results would be helpful in accurately assessing the impacts of forest ecosystems on regional water cycling, and provide scientific and practical implications for water resources management.

The modelling of rainfall interception in growing and dormant seasons for a pine plantation and a black locust plantation in semi-arid Northwest China

Interception loss can remove a significant portion of rainwater from forested ecosystems. Therefore, the quantification and modelling of interception loss are of significant importance if human and ecosystem water demands are to be balanced under a future changing climate. This is particularly true for semi-arid/arid regions, where afforestation has become an important ecological restoration measure to tackle desertification, poverty and climate change. However, quantification and modelling of interception loss of plantations in these regions have rarely been reported. In the present study, rainfall interception loss was quantified and modelled over a one-year period (January-December 2016) for a deciduous broad-leafed R. pseudoacacia plantation and an evergreen needle-leaf P. tabuliformis plantation (common afforestation tree species) situated in the semi-arid Loess Plateau of China. The stand age, density, canopy cover and leaf area index of R. pseudoacacia during the study period were 15 years, 2000 tree ha−1, 0.48 and 1.41 m2 m−2, respectively. The corresponding values for Pinus tabuliformis were 17 years, 1200 tree ha−1, 0.62 and 2.53 m2 m−2. The measured throughfall, stemflow and derived estimates of interception loss for R. pseudoacacia were 81.1%, 1.3% and 17.6%, respectively. The corresponding values for P. tabuliformis were 75.4%, 0.7% and 23.9%. Given that the weather conditions experienced by the two forest stands were similar, the observed higher interception loss for P. tabuliformis can be explained by the higher canopy storage capacity and wet canopy evaporation rate of this species. The revised Gash analytical model of rainfall interception was well calibrated and validated against field measurements and was able to simulate the cumulative interception loss at two forest stands accurately, and it also effectively captured the seasonal variation (leafed growing and leafless dormant seasons), provided that the optimized wet-canopy evaporation rates were used. The revised model was highly sensitive to the canopy storage capacity and changes in the ratio of mean wet canopy evaporation to mean rainfall intensity and less sensitive to canopy cover, but it was found to be fairly insensitive to the trunk storage capacity.

Rainfall partitioning measurement and rainfall interception modelling in a tropical semi-deciduous Atlantic forest remnant

Understanding the interaction between the hydrological cycle and native forests is essential to improve watershed management and support ecological services. The objectives of this study were to analyse and evaluate rainfall interception models applied to an ecosystem from the Brazilian Atlantic Forest Biome (BAFB), classified as “Montane Semi-Deciduous Forest.” The variables Gross Rainfall (P) (rainfall that reaches the canopy), Throughfall (Tf), Stemflow (Sf), and Interception Loss (I) were measured from September 2012 to March 2015. Weather variables were quantified above the canopy by a weather station and then used for canopy evaporation estimation. This estimation was based on two approaches: the slope of the linear regression of gross rainfall against interception, or the Gash procedure (Ev1), and the Penman–Monteith equation (Ev2). Two rainfall interception models (Liu and Gash) were employed, using both Ev1 and Ev2. Thirty-two fixed rain gauges were used for Tf measurements and 32 trees were selected across species and diameter at breast height ranges for Sf observations. The revised version of the analytical Gash model underestimated I by -17.5% and -11.1% for Ev1 and Ev2, respectively, resulting in less accurate estimates. Based on these relative errors, the performance of the Gash model was classified as “fair.” The Liu model overestimated I by 5.3% and 11.3% for Ev1 and Ev2, resulting in assessments of “good” and “fair” respectively, and thus indicating improved performance compared to the Gash model. Therefore, the Liu model coupled with Ev1 is preferable for simulation of rainfall interception in semi-deciduous forests of the BAFB. However, slight overestimation bias was observed, and the model requires tweaking with respect to the estimation of forest storage capacity for this ecosystem. Interception loss modelling is a strategic tool for assessing the influence of different weather patterns and forest vegetative features on water balance in semi-deciduous forest ecosystems.

THE MAIN PURPOSE FOR THE APPLICATION OF DOUBLE LAYER TIPPING BUCKET SENSORS IN RAINFALL MEASUREMENTS

The aim of this study was to investigate the main purpose for the application of double layer tipping bucket sensors based on the existing double layer tipping bucket sensor in Tegal Climatological Station, Indonesian Agency for Meteorology, Climatology, and Geophysics. Hydraulic to electric analogy and rainfall interception models from Calder, Rutter, and Gash were used as the investigation method. The result showed that double layer tipping bucket sensors were dedicated to measure high intensity rainfalls.

Modelling rainfall interception by urban trees

Trees in the urban environment have significant effects on the hydrological cycle by aiding in the reduction of stormwater runoff through rainfall interception. Factors such as wind exposure, relative humidity and leaf area index in the urban environment differ from those in a forest and affect the processes occurring within the canopy of conifers and deciduous tree species differently. This study focused on the interception losses of trees in an urban setting with a view to providing some information on tree selection in urban environments. An analytical model was formulated based on a rainfall interception model developed for sparse canopy forests and preliminary data on water losses from tree canopy interception. The model was validated using empirical data, and an assessment of the performance of the model for four deciduous tree species (white oak, Norway maple, green ash and Prunus sp.). Model-calculated values of interception losses and throughfall were congruent with measured empirical values. Sensitivity analysis with respect to model parameter values revealed that evaporation and rainfall rates were the most sensitive parameters for model output. The ratio of evaporation rate to rainfall rate used in the model was identified as the most dynamic parameter. To measure independently the two components requires further analysis, and a more reliable measurement of leaf area index.

Fitting rainfall interception models to forest ecosystems of Mexico

Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models—the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)—using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally <5.8% and Nash-Sutcliffe efficiency E estimators >0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and a benchmark for future investigations in this area of hydrology.

Canopy wetness patterns in a Mediterranean deciduous stand

Summary This study provides detailed information on the canopy drying process subsequent to rainfall events in a Mediterranean deciduous stand. Since this is a study of a deciduous forest ( Quercus pubescens Willd.), it has been possible to assess the differences in canopy structure as well as in meteorological conditions between seasons. Results show clear seasonal differences in wetness duration during the drying phase after rainfall, with longer wetness duration in the leafed period (8 h) than in the leafless one (4 h). There is better canopy ventilation in the leafless season, increasing canopy boundary layer conductance. However, there is a wind shelter effect in the leafed season, which entails low turbulence transfer within the canopy. Likewise, canopies remain wet longer at night in both seasons, but the differences in wetness duration between day and night are greater in the leafless season. Finally, the results indicate that the methods commonly used to separate rainfall events give an erroneous indication of the real canopy drying duration. This leads to inaccuracy in the number and duration of rainfall events and, thus, in their properties (such as rainfall depth and intensity) and represents a challenge to rainfall interception models.

Rainfall interception by natural and planted forests in the Middle Mountains of Central Nepal

► Rainfall interception loss was measured and modelled for natural and planted forest. ► The difference in rainfall interception loss between the two forests was examined. ► The model simulates interception loss well under monsoonal montane conditions. ► The difference in interception loss is due to differences in LAI and tree density. ► The high annual interception loss from planted forest could affect dry season flows. Measurements of gross rainfall, throughfall and stemflow were made during the 2011 rainy season in an evergreen natural forest and in a planted pine forest located in complex topography in the Middle Mountains of Central Nepal. For the period of observation (20 June–9 September, 2011), measured throughfall, stemflow and derived interception loss in the natural forest were 76.2%, 1.4% and 22.4% of incident rainfall, respectively. Corresponding values for the pine plantation were 83.0%, 0.5% and 16.5%. The revised version of Gash’s analytical model of rainfall interception was calibrated and validated for the two stands, representing a first for montane sub-tropical monsoonal conditions. The results of the modelling corresponded well with observed values, provided an optimised value was used for the average wet-canopy evaporation rate. The model was subsequently used to calculate annual interception losses from the two forests. Modelled estimates of annual interception loss for the planted and natural forest were 291 mm and 319 mm and represented 19.4% and 22.6% of incident rainfall, respectively. The high interception loss from the planted forest is considered a contributory factor towards the observed decline in dry season streamflow following the reforestation of degraded hillsides in the Middle Mountains of Nepal.

Simulation of Eco-hydrological Process in Hani Terrace wetland

Hani terrace is a precious legacy which Hani people created from generation to generation; it has been in good running for over thousand years. It is a complete new attempt to reveal the good running mechanism of Hani terrace from the eco-hydrological process, which is to reveal the terrace's interactive influence relationship with local ecological effect from the core of its hydrological element. In this article, on the basis of eco-hydrology process, the paper initially constructs a rainfall interception model, evapotranspiration model, plant - soil moisture transmission model, groundwater model, and eco-hydro-chemistry process simulation model, finally finds out initially ecological effect of Hani terrace wetland based on all models.

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979–present. This study introduces a supplemental and improved set of land surface hydrological fields (“MERRA-Land”) generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Modelling rainfall interception loss in forest restoration trials in Panama

AbstractA modified Liu analytical model of rainfall interception (Ic) by tree canopies was evaluated using rainfall, throughfall and stemflow data collected from forest restoration trials in the Republic of Panama. The model uses an introduced approach to estimating the water storage capacities of tree boles, which has a more realistic physical basis than earlier iterations of the Liu model. Study species (Acacia mangium, Gliricidia sepium, Guazuma ulmifolia, Ochroma pyramidale, and Pachira quinata) were selected on the basis of differing leaf size and crown characteristics. Significant interspecific differences in both observed and simulated cumulative interception loss were found, with A. mangium intercepting more rainfall than other species. Errors between calculated and modelled cumulative Ic ranged from + 6·3% to + 30·5%, with modelled Ic always being the larger term. During‐event evaporation rates from the study trees were positively related to tree height, crown area, and basal diameter. Crown area and the storage capacity of tree boles were negatively correlated. The results of a sensitivity analysis suggested that the modified model was most sensitive to variations in during‐event evaporation rate. The implications of the model's sensitivity to during‐event evaporation and the importance of this mechanism of interception loss are discussed, while suggestions are provided that may lead to further improvements to the analytical model. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Fraction of incident rainfall within the canopy of a pure stand of Pinus armandii with revised Gash model in the Liupan Mountains of China

Summary The throughfall, stemflow and interception during the growing season (June–September) of 2005 were observed in a pure stand of natural Pinus armandii forest in the Liupan Mountains of northwestern China. The results indicate that of the 544.0 mm of cumulative gross rainfall generated by 15 sampled events, throughfall, stemflow and canopy interception were 462.2 mm (84.96%), 4.8 mm (0.88%), and 77.0 mm (14.15%), respectively. The revised Gash analytical model of rainfall interception was employed and the simulated interception values were close to the observed with an underestimation of 5.87%. Moreover, 39.48% and 55.24% of interception were evaporated from canopy in the stages of “during storms” and “after storms”, respectively. The revised Gash analytical model is highly sensitive to changes regarding canopy storage capacity (S), cover (c) and the climate parameters of rainfall intensity R and evaporation E ¯ .