Modeling canopy interception under drought conditions: The relevance of evaporation and extra sources of energy

Rodrigues, André Ferreira; Mello, Carlos Rogério de; Nehren, Udo; Ribeiro, João Pedro de Coimbra; Mantovani, Vanessa Alves; Mello, José Márcio de

doi:10.1016/j.jenvman.2021.112710

Cited by 10 publications

(8 citation statements)

References 44 publications

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“…Note that this impact has not been observed across the last 58 years of precipitation records. Furthermore, seasonally, in the last decade (2010-2020), the records indicate a reduction in the total precipitation during the rainy period, as observed by [49] for Lavras (station 1). This impact might reflect changes in the precipitation regime due to climate change over the region.…”

Section: Discussionmentioning

confidence: 55%

Climate Change Impacts on Water Resources of the Largest Hydropower Plant Reservoir in Southeast Brazil

Mello

Vieira

Guzmán

et al. 2021

Water

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Approximately 70% of all the electric energy produced in Brazil comes from hydropower plants. In this context, the Grande River Basin (GRB) stands out in Brazil. Some studies have been carried out to investigate the impacts of climate change in tropical regions to support water resources’ management and planning. This study aims to project the changes in the runoff that feed the Furnas Hydropower Plant (FHP) reservoir (GRB-Furnas basin), the largest and most important facility in Southeast Brazil. The lavras simulation of hydrology model (LASH) was used to project the impacts on runoff and hydrological droughts over the century in GRB-Furnas. The regional climate models (RCMs) Eta-HadGEM-ES, Eta-MIROC5, and Eta-CanESM2 forced the LASH model from 2007 to 2099, taking the representative concentration pathways (RCPs) 4.5 and 8.5. LASH simulated the runoff adequately for the baseline period (1961–2005) using the RCMs’ outputs. A noticeable reduction in precipitation was identified in the wet season, especially in the 2007–2040 period for RCP4.5 and in the 2071–2099 period for RCP8.5. As a result, a significant reduction in the runoff, mainly in the baseflow, and an increase in droughts’ severity were projected throughout the XXI Century, which may compromise the water security to the FHP reservoir.

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Section: Discussionmentioning

confidence: 55%

Climate Change Impacts on Water Resources of the Largest Hydropower Plant Reservoir in Southeast Brazil

Mello

Vieira

Guzmán

et al. 2021

Water

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“…Similar to the RGAM, the Liu model also underestimated the I c (Tables 5 and 6). Rodrigues et al (2021) also compared the performances of the RGAM and Liu model, and found the Liu model performed better with an underestimation of 0.85%. This might be due to the fact that their study was carried out in tropical forests and the storage capacity between the canopy and trunk was split in the RGAM in their study (Rodrigues et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…The E was calculated as the product of R and the regression slope of P g versus I c (a). Previous studies have shown E obtained by this method is more accurate than when calculated using the Penman-Monteith equation (Ma et al, 2019;Ma et al, 2020;Rodrigues et al, 2021). The possible reasons are discussed below.…”

Section: Interception Parametersmentioning

confidence: 95%

“…Rodrigues et al (2021) also compared the performances of the RGAM and Liu model, and found the Liu model performed better with an underestimation of 0.85%. This might be due to the fact that their study was carried out in tropical forests and the storage capacity between the canopy and trunk was split in the RGAM in their study (Rodrigues et al, 2021). NSE values for the Liu model were consistently lower than for the RGAM (Tables 5 and 6), and the RMSE between the measured and simulated I c was consistently higher for the Liu model but had a maximum value of 0.64 mm.…”

Section: Performance Of the Rgam And Liu Modelmentioning

confidence: 99%

“…For example, Návar (2017) found the RGAM estimated the I c in temperate forests better than the Liu model, with mean deviation efficiencies of −2.50% and −4.64% for the RGAM and Liu model, respectively. However, the Liu model performed better in tropical forests, underestimating the I c by only 0.85% compared to RGAM overestimating the I c by 4.6% (Rodrigues et al, 2021). Thus, the applicability of the two models should be tested in more regions.…”

Section: Introductionmentioning

confidence: 99%

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Comparisons of rainfall partitioning and canopy interception modelling in pure and mixed forests on the Chinese Loess Plateau

Wu,

Zhu,

Zhang

et al. 2024

Hydrological Processes

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Rainfall partitioning is a key process in forest ecosystems that affects the forest hydrological cycle and ecological services. However, little is known about the rainfall partitioning in Pinus tabuliformis (PT), Robinia pseudoacacia (RP), and Pinus tabuliformis×Robinia pseudoacacia (PT × RP) forests, which are widely distributed on the Chinese Loess Plateau (CLP) for controlling soil and water losses. The objectives of this study were to compare the rainfall partitioning and conduct interception modelling in PT, RP, and PT × RP forests, using data from the Ansai and Changwu sites on the CLP. The sites feature similar weather conductions and both pure and mixed forests of the same age. The tree density of PT × RP was moderate at the Ansai site but higher at the Changwu site compared to PT and RP. We quantitatively measured the throughfall (Tf), stemflow (Sf), and interception loss (Ic) for the forests at the two sites during the growing season (May–October, 2022), and simulated Ic using the Revised Gash Analytical Model (RGAM) and Liu model. The results showed that measured Ic for PT × RP (26.0% of the total gross rainfall, Pg) was larger than for RP (22.0% of Pg) but smaller than for PT (27.8% of Pg) at the Ansai site, and vice versa for the Tf and Sf (RP > PT × RP > PT), while the measured Ic for PT × RP (33.7% of Pg) at the Changwu site was larger than both for PT (31.1% of Pg) and RP (19.5% of Pg). The Tf and Sf for PT × RP was smaller than for PT and RP. Given the similar weather conditions, differences in Ic for the pure and mixed forests at each site were attributed to canopy storage capacity, wet canopy evaporation rate, and tree density. Additionally, the RGAM and the Liu model effectively simulated and captured the differences in Ic for PT, RP, and PT × RP. However, the RGAM performed better with a relative error less than −7.3%, Nash‐Sutcliffe model efficiency ranging from 0.82 to 0.95, and root mean square error less than 0.5 mm. According to the RGAM, evaporation from the wet canopy during rainfall events and after rainfall cessation were the two most influential components. The results of this study suggest that mixed forest can optimize rainfall partitioning compared to pure forests, but a reasonable density should be adopted to increase rainwater replenishment to the forest floor.

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Modelling rainfall interception losses of three plantations in the Loess Plateau

Wei,

Song,

et al. 2024

Hydrological Processes

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The forest canopy affects the water entering the forest ecosystem by intercepting rainfall. This is especially pertinent in forests that depend on rainfall for their ecological water needs, quantifying and simulating interception losses provide critical insights into their ecological hydrological processes. In the semi‐arid areas of the Loess Plateau, afforestation has become an effective ecological restoration measure. However, the rainfall interception process of these plantations is still unclear. To quantify and model the canopy interception of these plantations, we conducted a two‐year rainfall redistribution measurement experiment in three typical plantations, including a deciduous broadleaf plantation (Robinia pseudoacacia) and two evergreen coniferous plantations (Platycladus orientalis and Pinus tabuliformis). Based on this, the revised Gash model was used to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. The experiment clarified the rainfall redistribution in the three plantations, and the proportions of throughfall to gross rainfall in Robinia pseudoacacia, Platycladus orientalis, and Pinus tabuliformis were 84.8%, 70.4%, and 75.6%; corresponding, the stemflow proportions were 2.0%, 2.2%, and 1.8%; the interception losses were 13.2%, 27.4%, and 22.6%, respectively. The dominant rainfall pattern during the experiment was characterized by low‐amounts, moderate‐intensity, and short‐duration, during which the highest interception proportions across the three plantations were observed. We used the Penman‐Monteith equation and the regression method, respectively, to estimate the canopy average evaporation rate of the revised Gash model, finding that the latter provides a closer match to the measured cumulative interception (NSE >0.7). When simulating interception under the three rainfall patterns, the model with the regression method better simulated the cumulative interception and event‐scale interception for Platycladus orientalis and Pinus tabuliformis plantations under the dominant rainfall pattern. The results contribute valuable information to assess the impact of forest rainfall interception on regional hydrologic processes.

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Modeling canopy interception under drought conditions: The relevance of evaporation and extra sources of energy

Cited by 10 publications

References 44 publications

Climate Change Impacts on Water Resources of the Largest Hydropower Plant Reservoir in Southeast Brazil

Climate Change Impacts on Water Resources of the Largest Hydropower Plant Reservoir in Southeast Brazil

Comparisons of rainfall partitioning and canopy interception modelling in pure and mixed forests on the Chinese Loess Plateau

Modelling rainfall interception losses of three plantations in the Loess Plateau

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