Relationships between rainfall parameters and interception by tropical forest

doi:10.1016/0022-1694(75)90082-7

Journal of Hydrology

Volume 24, Issues 3–4, February 1975, Pages 215-238

https://doi.org/10.1016/0022-1694(75)90082-7 Get rights and content

Abstract

The process of rainfall interception by vegetation is discussed. Using data from an East African experiment, relationships between interception and various rainfall parameters are analysed and the reliability of predictive equations assessed. Simple relationships appeared to be as valid for prediction as more complex ones, although in general the results were rather unsatisfactory.

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Cited by (122)

Estimating rainfall interception loss of three dominant shrub species in an oasis–desert ecotone using in situ measurements and the revised Gash analytical model
2023, Journal of Environmental Management
Canopy interception loss affects the local water budget by removing a non-negligible proportion of rainfall from the terrestrial surface. Thus, quantifying interception loss is essential for thoroughly understanding the role of vegetation in the local hydrological cycle, especially in dryland ecosystems. However, sparse shrubs in dryland ecosystems have not been sufficiently studied, owing to time- and labor-intensive field experiments and challenging model parameterization. In this work, 4-year growing season field experiments on rainfall partitioning were conducted for three dominant shrub species (Haloxylon ammodendron, Nitraria sphaerocarpa, and Calligonum mongolicum) in an oasis–desert ecotone in northwestern China. The revised Gash analytical model was well parameterized, which reliably simulated the cumulative interception loss for sparse shrubs, and the validated model performed better for H. ammodendron, followed by C. mongolicum and N. sphaerocarpa, with relative errors of 8.4%, 15.4%, and 23.9%, respectively. The mean individual interception loss percentage for H. ammodendron (28.4%) was significantly higher than that for C. mongolicum (11.0%) and N. sphaerocarpa (10.9%) (p < 0.05), which could be ascribed to the higher canopy storage capacity and wet-canopy evaporation rate of H. ammodendron. For all shrub species, the majority proportion of interception loss occurred during canopy saturation and drying-out periods, accounting for approximately 79–85% of the cumulative interception loss. Overall, the mean local interception loss of three dominant shrub species in the ecotone removed nearly 17% of the corresponding cumulative rainfall during the growing season. These results not only provide methodological references for estimating the interception loss of sparse vegetation in dryland ecosystems, but also provide scientific insights for water resource management and ecosystem restoration in water-limited regions similar to the experimental site.
The performance of the reformulated Gash rainfall interception model in the Hyrcanian temperate forests of northern Iran
2022, Journal of Hydrology
Citation Excerpt :
Understanding the relationship between the canopy water balance and the different forest species would play an important role in accurately predicting how plantation with new species affects I and water resources. A variety of I process models, ranging from simple empirical-type models (Jackson, 1975) and probabilistic models (Calder, 1977) to the sophisticated data-demanding model –like Gash-type models (Gash, 1979; Gash et al., 1995) are currently available for making I predictions (see the review paper by Muzylo et al., 2009). The Gash (Gash, 1979) and revised versions (Gash et al., 1995; Valente et al., 1997) are the most commonly used models for estimating I in forested ecosystems (see review by Muzylo et al., 2009).
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 ( $\bar{E} / \bar{R}$ ; 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.
Testing three rainfall interception models and different parameterization methods with data from an open Mediterranean pine forest
2022, Agricultural and Forest Meteorology
Citation Excerpt :
Obviously, the derivation of the model parameter values with the regression method implies that evaporation before canopy saturation is not a function of the depth of water on the canopy. In contrast to the approach by Jackson (1975), who assumed that evaporation is negligible during the storm, we assume a constant evaporation rate during the entire rainfall event. We used the daily TF and P data from 01/Jul/2016 to 31/Dec/2018 to derive the model c, S and Ēc/R̄.
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 (Ē_c/R̄) and potential evaporation (E_o). 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 Ē_c/R̄. Test runs with different combinations of S, c and Ē_c/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.
The ecohydrological function of the tropical forest rainfall interception: Observation and modeling
2022, Handbook of HydroInformatics: Volume II: Advanced Machine Learning Techniques
Forests provide important ecosystem services, several of them related to water. The interconnections between rainfall interception and the water cycle vary among the forest types. Tropical forests are one of the most relevant biodiversity shelters, with several endemic plant and animal species. These forests provide key ecohydrological services by directly acting on biogeochemical cycles and water supply. Understanding these interconnections is crucial for better planning forest conservation and reforestation initiatives, especially under climate change conditions. Therefore, a set of techniques and devices is required to monitor rainfall–forest interface processes in tropical forests as they are very complex ecosystems. In this chapter, we intend to assess rainfall-forest interface processes as well as some of the methods that have been used for quantifying rainfall interception in forests, contributing to the ecohydrological studies.
Modeling canopy interception under drought conditions: The relevance of evaporation and extra sources of energy
2021, Journal of Environmental Management
Modeling canopy interception is fundamental for understanding the forests’ role in local and regional hydrology. In this study, canopy interception (CI), throughfall (TF), and stemflow (SF) were evaluated for a semi-deciduous Atlantic Forest (AFR) from 2013 to 2019, where a prolonged dry period occurred. The Gash and Liu models were analyzed in detail to determine the most appropriate for modeling CI throughout drought conditions. Thus, the climatic parameters were retrieved annually by a modified TF-based method (E_I%), whereas the structural parameters represented the entire period. The contribution of the energy stored in the forest (i.e. air and biomass; Q) to CI was also assessed in the AFR stand. Both models performed well when using E_I%, as the Gash model overestimated CI by 71 mm (4.6%), whereas the Liu model underestimated it by only 13 mm (0.85%). This performance is due to an increased Q and turbulent mechanisms (such as advection and strong updrafts) that occur in drought conditions and are indirectly accounted for in E_I%. However, the Liu model stood out for modeling CI under a prolonged dry period, as the exponential wetting approach better represents the complex canopies of the semi-deciduous forests. Thus, we recommend the Liu model and additional energy sources when dealing with prolonged droughts, as in the case of climate change scenarios projected to the studied region.
Comparative modeling of the effect of thinning on canopy interception loss in a semiarid black locust (Robinia pseudoacacia) plantation in Northwest China
2020, Journal of Hydrology
Canopy interception loss is a key component of forest hydrological cycle that determine the amount of net rainfall reaching forest floor together with drought/climate stressors affecting dryland forest plantations. A good understanding of the relationship between canopy interception loss and forest management such as thinning is important for improved watershed management and ecological services. In this study, we measured event-based rainfall partitioning for a thinned (TH, with 38% basal area removed) and a control (CT) Robinia pseudoacacia forest plantation during leafed and leafless seasons in 2015 in the semiarid Loess Plateau region in China. Interception loss from both forest plots were simulated using the Revised Gash Analytical Model (RGAM) and the WiMo model. The results showed that observed annual throughfall, stemflow and interception loss were respectively 80.8%, 1.7% and 17.5% of the gross rainfall under CT. The corresponding values under TH were 87.9%, 0.8% and 11.3%, respectively. The RGAM and WiMo models were well calibrated and validated using filed data collected in leafed and leafless seasons. The analyses suggested that models accurately predicated interception loss under both CT and TH conditions and captured seasonal variations in canopy and meteorological parameters. The RGAM model was most sensitive to the ratio of mean evaporation rate to mean rainfall intensity, and canopy storage capacity in leafed season, and to the ratio of mean evaporation rate to mean rainfall intensity in leafless season. Moreover, 37.2% and 42.1% of the interception in leafed season evaporated from the canopy respectively during rainfall event and after rainfall. The corresponding values for leafless season were respectively 49.3% and 22.4%. Overall, the performance of the optimized RGAM and WiMo models were satisfactory with respect to modeling error (−6.9 − −2.9%) and Nash-Sutcliffe model efficiency (0.80–0.94), although that of the optimized RGAM model was slightly superior to WiMo model. The models would facilitate the implementation of water-oriented management in semiarid forest plantations through a more accurate simulation of the impact of thinning on interception loss.

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Relationships between rainfall parameters and interception by tropical forest

Abstract

J. Hydrol.

J. Hydrol.

Interception and soil-moisture distribution

Beobachtungen über den Verbleib von Niederschlägen im Urwald und den Einfluss von Waldbestand auf den Wasserhaushalt der Umgebung

Forstwiss. Zentralbl.

Climate Near the Ground

Design criteria for interception studies

Rainfall interception

Mon. Weather Rev.

Measurement of rainfall interception by tropical highland forest

Role of Hydrology and Hydrometeorology in the Economic Development of Africa, 11

W.M.O. Publ.

Measurement of rainfall, interception and evaporation losses in a plantation of Sitka spruce trees

Assoc. Int. Hydrol. Sci., Assem. Gen. de Toronto

Mathematical theory of interception

Rainfall interception in forest and moorland

Tropical Soils