Canopy Resistance Research Articles

Actual transpiration and canopy resistance in a Mediterranean vineyard irrigated with saline water

Irrigation with saline water is practiced in countries prone to water scarcity, in arid and semi-arid climates. In a Mediterranean climate (Sicily, southern Italy), transpiration and canopy resistance were determined in a vineyard (Syrah grafted on Paulsen 1103) irrigated with water at two salinity levels. One section of the experimental plot was irrigated with water of low salinity (electrical conductivity ECw = 0.6 dS m−1); the other section received irrigation water at higher salinity level (ECw = 1.6 dS m−1). Actual vines transpiration was measured by a thermal dissipation sap flow method, in two growing seasons (2008 and 2009). Canopy transpiration (Tr) and resistance (rc), the latter calculated using the Penman–Monteith equation, were analyzed on hourly and daily time scale. Moreover, the trends in canopy resistance were evaluated in relation to main micrometeorological variables (global radiation and vapor pressure deficit). In the ECw 1.6 treatment, canopy transpiration was lower and its values, cumulated through the experimental period, were 20% and 16% lower than in the ECw 0.6 treatment, in 2008 and 2009, respectively. A rudimentary estimate of the relationship between cumulated canopy transpiration and soil salinity was also made, and a threshold value of relative transpiration was identified at soil electrical conductivity (ECe) = 1.4 dS m−1. Hourly values of rc in ECw 1.6 were higher than in ECw 0.6 and the response patterns of rc to global radiation and to vapor pressure deficit were different at different salinity levels.

Estimation of Aerodynamic and Canopy Resistances in a Mediterranean Greenhouse Based on Instantaneous Leaf Temperature Measurements

Aerodynamic and canopy resistances have long been considered to be of key interest in model equation parameterization, particularly for the accurate estimation of crop evapotranspiration. However, model parameters applied in greenhouses showed variation affected by the micrometeorological environment. Three experiments were carried out in a plastic greenhouse to evaluate microclimate effects on resistances of a soilless cucumber crop. The regression analysis of canopy-to-air temperature (Tc − Ta) difference on air vapor pressure deficit (VPD) was substituted into the energy balance equation for the estimation of aerodynamic and canopy resistance values. As expected, a fan and pad evaporative cooling system proved to be the more efficient method of decreasing crop temperature (Tc) compared to the forced air ventilation system. The estimated transpiration by the Penman–Monteith model based on calculated aerodynamic and canopy resistance values successfully validated values measured with lysimeters in different growing periods. In this article, we report for the first time the calculation of aerodynamic and canopy resistance values inside a greenhouse based on equations for an open field that were found in the literature. Results may be helpful in Mediterranean greenhouses for direct determinations of plant water evaporative demand and smart climate control systems.

A comparison of two bidirectional air-surface exchange models for gaseous elemental mercury over vegetated surfaces

Uncertainties exist in the current estimates of atmospheric dry deposition and air-surface exchange of atmospheric mercury in chemical transport models and monitoring networks. To quantitatively assess these uncertainties, two bidirectional air-surface exchange models for gaseous elemental mercury (Hg0), originally developed by Wang et al. (2014, Atmos. Chem. Phys., doi:10.5194/acp-14-6273-2014) and Wright and Zhang (2015, J. Adv. Model. Earth Syst., doi:10.1002/2014MS000367), were compared quantitatively. The two models were applied to two vegetated land covers, including a deciduous broadleaf forest and a cropland, near a monitoring site in Georgia, USA for calculating air-surface exchange fluxes of Hg0. The model inputs include measured 2-hourly ambient Hg0 concentrations and archived surface meteorology data produced from a weather forecast model. The estimated annual net fluxes differed significantly between the two models, i.e., −0.7 μg m−2yr−1 by Wang et al.’s model vs. −8.6 μg m−2yr−1 by Wright & Zhang's model over the deciduous broadleaf forest and 8.4 μg m−2yr−1 vs. −10.7 μg m−2yr−1 over the cropland. When considering dry deposition and emission fluxes separately, similar deposition fluxes were produced by the two models, regardless of season and land cover, due to the similar canopy resistance formulas used in the two models. Much higher soil and lower stomatal emission fluxes were produced by Wang et al.’s model than Wright & Zhang's model (soil: 30 vs. 8.9 μg m−2yr−1 and stomata: 0.5 vs. 8.3 μg m−2yr−1, averaged over the two canopies) due to the very different emission potentials used in the two models. Cuticle emission fluxes contributed less than 0.1% to the total emission flux in Wang et al.’s model, and were not considered in Wright & Zhang's model. The differences in soil emission flux, total emission flux, and net flux were more pronounced in winter than in the other seasons. The large differences in the net fluxes between the two models were primarily caused by their very different schemes of soil emission potential.

Modelling evapotranspiration in off-line simulations of greenhouse climate control

The design of greenhouse environmental control involves simulations under various climate and system configuration alternatives. These off-line model-based simulations cannot use online measured greenhouse conditions (temperature, humidity) and must rely on historical weather data and on well-established greenhouse and crop properties. An important element of such simulations is the partitioning of the dissipated energy into sensible and latent heat, which can be achieved in different ways. Specifically, the rate of evapotranspiration (ET) may be obtained from 1) knowledge of the aerodynamic and stomatal canopy resistances, 2) estimating ET from atmospheric conditions and control settings, or 3) estimating the Bowen (sensible to latent heat) ratio in the ventilation stream (VBR) from the atmospheric conditions. The objective of this study is to compare the simulated behaviour of a tomato greenhouse, based on these three quite different approaches, both among themselves and against a full-year data set from a commercial Dutch cherry-tomato greenhouse. Using a quasi-steady-state simulation-optimization program with hourly time steps, trajectories of indoor conditions (temperature, humidity, CO2 concentration), control actions (heating, ventilation, CO2 enrichment, thermal screen), yield and ET were obtained, and their monthly averages presented. At the monthly time scale the simulated results are very similar among themselves and to those observed, with the exception that the simulated summer CO2 concentrations, and hence fruit yield, are higher than those observed, possibly due to the optimization inherent in the simulations. The considerable VBR discrepancy between the three ET formulations during autumn is due to low nighttime ET, but this has a negligible effect on the daily calculated ET. In conclusion, it seems that for off-line design purposes a simple linear dependence of ET on global radiation is sufficient. Adaptation of the model to existing facilities may require a more refined version of the VBR approach.

Comparison of two canopy resistance models to estimate evapotranspiration for tea and wheat in southeast China

Actual evapotranspiration (λET) can be estimated with meteorological parameters using the Penman-Monteith (PM) model where the canopy resistance (rc) plays an important role but is difficult to determine. The Katerji-Perrier (KP) and Todorovic (TD) models are widely used to determine the rc. A comparative study was conducted to evaluate the performances of two models, on hourly and daily scales, in simulating the λET for a tea and a wheat field in southeast China. The estimated λET was compared with the measured λET by the Bowen ratio energy balance (BREB) method. The results indicated that the KP model simulated the λET of tea and wheat well for both hourly and daily scales, while the TD model simulated the λET well for the wheat for both time scales but significantly overestimated the tea λET by 44.9%. Therefore, the KP model was preferred to estimate λET for both crops, the TD model should be avoided in tea fields.

Remotely sensed canopy resistance model for analyzing the stomatal behavior of environmentally-stressed winter wheat

Stomata is an important channel for the exchange of water and gas between crops and the external environment. Stomatal behavior can shed light on how environmental stressors affect crop growth. Traditional stomata investigation methods involve experimental laboratory measurements of specific plants using stoma-related instruments or a field plot. However, developing a new remote sensing canopy resistance model for analyzing the stomatal behavior of crops under typical environmental stress is essential for regional agricultural management. Canopy resistance is a vital microscale–macroscale (from kilometers to micrometers) bridge that represents the stomatal behavior of the entire crop. In this study, a remote sensing canopy resistance model was proposed based on the Penman-Monteith model and a remote sensing evapotranspiration model. The model was verified by field-observed winter wheat data at the Yucheng Comprehensive Experiment Station (YCES) with dry-hot wind (DHW) and brackish water irrigation treatments from 2017 to 2019. The model measured canopy resistance (regression coefficient = 1.25; R2 = 0.98) well. Finally, remote sensing-based canopy resistance measurements were used to investigate the effects of soil salinity and dry-hot wind on the winter wheat. The results showed excellent model performance for retrieving crop stomatal behavior under two environmental stresses and proved that the proposed remote sensing canopy resistance model is a promising tool for the investigation of stomatal behavior under environmental stress; this is particularly relevant for regional precision farming.

Modeling rice evapotranspiration under water-saving irrigation condition: Improved canopy-resistance-based

Models capable of accurately calculating crop evapotranspiration (ET) are essential to improving water management at both the hydrological cycle and the agriculture irrigation project scale. Penman-Monteith (PM) and Shuttleworth-Wallace (SW) models based on the Jarvis-type canopy resistance (rc) model were used to calculate the hourly and daily ET of rice grown in East China under water-saving irrigation (WSI). The model parameters in rc and soil resistance (rss) were recalibrated to improve the accuracy of rice ET estimations. Notable, three improvements were made to the rc model: (i) model parameters were calibrated at the canopy scale, and a term of effective leaf area index was used to reflect the influence of canopy coverage; (ii) the coefficient a4 was used to reflect the influence of the specific soil moisture patterns under WSI practice; and (iii) for rice crops, soil moisture at saturation, rather than at field capacity for upland crops, served as a key parameter in the soil water response functions. Both PM and SW models generated similar rice ET outputs due to their common theoretical basis. Surprisingly, the PM model, with an appropriately adjusted rc value, performed better than the SW model in simulating hourly and daily rice ET under WSI practice, particularly during periods when canopy cover was either dense or sparse. Sensitivity analyses showed both models to be highly sensitive to changes in rc, and soil moisture (θ), the latter being one of the dominant contributors to variations in rc and rss. Accordingly, the PM model is recommended for the prediction of rice ET grown under WSI conditions in East China, with the caveat that both the rc and θ should be accurately quantified when used as inputs.

Temporal Upscaling of Rice Evapotranspiration Based on Canopy Resistance in a Water-Saving Irrigated Rice Field

AbstractAn important element of the hydrologic cycle, the hydrometeorological parameter of evapotranspiration (ET), is critical in the development of effective water resources planning and irrigation scheduling. The ET varies in response to changes in resistance at the canopy surface rc and soil moisture content θ, especially under water-saving irrigation (WSI) practices. Drawing on data collected by eddy covariance in WSI rice paddies in eastern China in 2015 and 2016, variations in ET were studied by calculating and analyzing hourly canopy resistance and daily canopy resistance . Discrepancies were noted between true daily ET with respect to the estimated daily ET at different periods [0700–1600 local time (UTC + 8)]. To estimate in the WSI rice fields, the mean value between 0900 and 1000 LT, and between 1000 and 1100 LT performed considerably better than for a single time. Seasonal estimated ET can be accurately calculated by interpolating at different time intervals, thereby achieving a greater correlation and consistency at 2-day intervals. Then a generalized two-segment line of variation was used to calculate , achieving good results and showing that in the absence of observational data, could be easily calculated through a simplified pattern of variability. In conclusion, an ET temporal upscaling method for a WSI paddy, based on variation in and values, was optimized and is recommended for local application. Future work will focus on temporal upscaling of ET by extrapolating remote sensing instantaneous estimates to daily values.

Evaluation of Noah-MP Land-Model Uncertainties over Sparsely Vegetated Sites on the Tibet Plateau

The water budget and energy exchange over the Tibetan Plateau (TP) region play an important role on the Asian monsoon. However, it is not well presented in the current land surface models (LSMs). In this study, uncertainties in the Noah with multiparameterization (Noah-MP) LSM are assessed through physics ensemble simulations in three sparsely vegetated sites located in the central TP. The impact of soil organic matter on energy flux and water cycles, along with the influence of uncertainties in precipitation are explored using observations at those sites during the third Tibetan Plateau Experiment from 1August2014 to31July2015. The greatest uncertainties are in the subprocesses of the canopy resistance, soil moisture limiting factors for evaporation, runoff (RNF) and ground water, and surface-layer parameterization. These uncertain subprocesses do not change across the different precipitation datasets. More precipitation can increase the annual total net radiation (Rn), latent heat flux (LH) and RNF, but decrease sensible heat flux (SH). Soil organic matter enlarges the annual total LH by ~26% but lessens the annual total Rn, SH, and RNF by ~7%, 7%, and 39%, respectively. Its effect on the LH and RNF at the Nagqu site, which has a sand soil texture type, is greater than that at the other two sites with sandy loam. This study highlights the importance of precipitation uncertainties and the effect of soil organic matter on the Noah-MP land-model simulations. It provides a guidance to improve the Noah-MP LSM further and hence the land-atmosphere interactions simulated by weather and climate models over the TP region.

Estimating Rice Panicle Temperature with Three-Layer Model

Rice panicle temperature (Tp) is a key factor for studying high temperature impacts on spikelet sterility. Comparing with measuring Tp by hand, a Tp simulation model could obtain Tp data readily. The two-layer energy budget model which divides the soil layer and canopy layer was widely used to predict rice canopy temperature (Tc), but panicle existed mostly in the upper layer canopy, and we have proved that Tc was different from the upper layer canopy temperature (Tc1), and the upper layer must be separated from the whole canopy for the purpose of estimating Tp. Thus, we developed the three-layer model, contained upper canopy layer with panicle (50–100 cm), lower rice canopy layer (10–40 cm), and water surface layer (≤10 cm) to estimate Tp with general meteorological and vegetation growth data. There were two steps to estimate Tp. The first step was calculating Tc1 and lower layer canopy temperature (Tc2) by solving heat balance equations with canopy resistances. And the second step was estimating Tp with following parameters: (a) the inclination factors of leaves and panicles (F1, F2, and Fp) which were decided by fitting the calculated transmissivity of downward solar radiation (TDSR) to the measured TDSR, (b) the aerodynamic resistance between the panicle and atmosphere (rap) denoted by wind speed, (c) the panicle resistance for transpiration (rp) denoted by days after heading, and (d) air temperature and humidity at the panicle’s height (Tac1 and eac1) calculated from the resistances of the pathways of sensible and latent heat fluxes in accordance with Ohm’s law. The model simulated fairly well the Tc1, Tc2, and Tp with root mean square errors (RMSEs) of 0.76°C, 0.75°C, and 0.81°C, respectively, where RMSE of measured Tp and predicted Tp by integrated micrometeorology model for panicle and canopy temperature (IM2PACT) including two-layer model was 1.27°C. This model was validated well by two other rice cultivars, and thus, it demonstrated the three-layer model was a new feasible way to estimate Tp.

Bayesian analysis of jujube canopy transpiration models: Does embedding the key environmental factor in Jarvis canopy resistance sub-model always associate with improving transpiration modeling?

The Jarvis canopy resistance sub-model is commonly used in transpiration modelling, although its optimal structure is rarely studied. It is still not fully clear that to what extent transpiration modeling may differ if using different constraint function forms for key environmental variable in Jarvis sub-model. In this study, various Jarvis canopy resistance sub-model configurations were embedded in the Penman-Monteith model to compare their ability to model daily transpiration of rain-fed jujube (Ziziphus jujuba Mill.) plantations where soil moisture is a key factor of tree water use. Parameters were calibrated using the Bayesian Markov Chain Monte Carlo (MCMC) simulation technique and model comparison was quantified using Deviance Information Criterion (DIC). The results showed significant differences in model performance between the constraint function forms of soil water content. The difference in DIC between the model with the best constraint function form and the other two forms reached 37.66–50.94, much higher than the evaluation criteria for significance (larger than 7). When the best constraint function form was used, the performance of the transpiration model improved. The model performance worsened when the other constraint function forms were used, even worse than those without consideration for soil water content. However, only slight differences in model performance were detected for the constraint function forms of temperature, vapor pressure deficit and photosynthetically active radiation. Using the best configuration of Jarvis canopy resistance sub-model, daily transpiration of jujube plantation was well estimated with overall good accuracy and acceptable uncertainty. The predictions and observations were highly correlated (R2 = 0.87 for calibration and R2 = 0.80 for validation). The results suggested that different constraint function forms of an environmental factor contributed differently to transpiration model performance, and the situation was different for different environmental factors. Including the key environmental factor in the Jarvis canopy resistance sub-model will not always improve the performance of transpiration models.

Estimating crop coefficients for apple orchards with varying canopy cover using measured data from twelve orchards in the Western Cape Province, South Africa

The FAO-56 crop coefficient (Kc) approach is widely used for making irrigation decisions. Allen and Pereira (2009) extended this approach by developing a method for estimating Kc using a density coefficient (Kd), which is estimated from the fraction of ground covered by vegetation and plant height. In this study we evaluated this method using detailed measurements of transpiration (T), evapotranspiration (ET), soil attributes, weather, and tree physiological variables in 12 apple (Malus domestica Borkh.) orchards in the Western Cape Province of South Africa. Mid-summer canopy cover of the orchards was less than 20 % in young non-bearing and exceeded 60 % in mature full-bearing orchards. Data were collected over three growing seasons (October 2014 to May 2017) in orchards planted to the Golden Delicious/Reinders®, Cripps Pink, Cripps Red, and Rosy Glow apple cultivars. The original Allen and Pereira (A&P) method significantly overestimated the basal crop coefficients (Kcb) by on average 47 % in mature and 103 % in young orchards, respectively. However, improved Kcb estimates were obtained by adjusting the ratio of the resistances (i.e. rl /100) in the A&P method, where rl is the mean leaf resistance and 100 s/m is the typical resistance for annual crops. We defined a resistance parameter “α” for apple orchards which is equivalent to the bulk canopy resistance of a well-watered tree. Replacing rl /100 with rl /α, and using the measured mean rl and other biophysical measurements to solve the A&P equation for α gave a value ∼ 37 s/m. The improved Kcb values were used to derive the orchard Kc taking into account the contribution of cover crops whose transpiration was measured using miniature stem heat balance sap flow gauges. The seasonal total transpiration (T) estimated as T = Kcb x ETo, where ETo is the reference ET closely matched the measured values with a RMSE (root of the mean square error) of ∼ ±16 mm. Therefore, using the mean canopy resistance which is representative of apple trees in the A&P method has the potential to accurately predict both the crop coefficients and water use of apple orchards from planting until full bearing age.

Parameterization and Application of Stanghellini Model for Estimating Greenhouse Cucumber Transpiration

Accurate estimation of transpiration (Tr) is important in the development of precise irrigation scheduling and to enhance water-use efficiency in agricultural production. In this study, the air temperature (Ta) and relative humidity (RH) were measured at three different heights (0.5, 1.0, and 1.8 m above the ground near the plant canopy) parameterize aerodynamic resistance (ra) based on the heat transfer coefficient method and to estimate Tr using the Stanghellini model (SM) during two growing seasons of cucumber in a greenhouse. The canopy resistance (rc) was parameterized by an exponential relationship of stomata resistance and solar radiation, and the estimated Tr was compared to the values measured with lysimeters. After parameterization of ra and rc, the efficiency (EF) and the Root Mean Square Error (RMSE) of the estimated Tr by the SM based on micrometeorological data at a height of 0.5 m were 95% and 18 W m−2, respectively, while the corresponding values were 86% and 29 W m−2 at a height of 1.8 m for the autumn planting season. For the spring planting season, the EF and RMSE were 92% and 34 W m−2 at a height of 0.5 m, while the corresponding values were 81% and 56 W m−2 at a height of 1.8 m, respectively. This work demonstrated that when micrometeorological data within the canopy was applied alongside the data measured above the canopy, the SM led to better agreement with the lysimeter measurements.

Canopy Resistance and Estimation of Evapotranspiration above a Humid Cypress Forest

This study presented a two-year data set of sensible heat and water vapor fluxes above a humid subtropical montane Cypress forest, located at 1650 m a.s.l. in northeastern Taiwan. The focuses of this study were to investigate (1) the diurnal and seasonal variations of canopy resistance and fluxes of sensible heat and water vapor above this forest; and (2) the mechanism of why a fixed canopy resistance could work when implementing the Penman–Monteith equation for diurnal hourly evapotranspiration estimation. Our results showed distinct seasonal variations in canopy resistance and water vapor flux, but on the contrary, the sensible heat flux did not change as much as the water vapor flux did with seasons. The seasonal variation patterns of the canopy resistance and water vapor flux were highly coupled with the meteorological factors. Also, the results demonstrated that a constant (fixed) canopy resistance was good enough for estimating the diurnal variation of evapotranspiration using Penman–Monteith equation. We observed a canopy resistance around 190 (s/m) for both the two warm seasons; and canopy resistances were around 670 and 320 (s/m) for the two cool seasons, respectively. In addition, our analytical analyses demonstrated that when the average canopy resistance is higher than 200 (s/m), the Penman–Monteith equation is less sensitive to the change of canopy resistance; hence, a fixed canopy resistance is suitable for the diurnal hourly evapotranspiration estimation. However, this is not the case when the average canopy resistance is less than 100 (s/m), and variable canopy resistances are needed. These two constraints (200 and 100) were obtained based on purely analytical analyses under a moderate meteorological condition (Rn = 600 W·m−2, RH = 60%, Ta = 20°C, U = 2 m·s−1) and a measurement height around two times of the canopy height.

Maize Evapotranspiration Estimation Using Penman-Monteith Equation and Modeling the Bulk Canopy Resistance

Some techniques, such as the Katerji and Perrier approach, estimate the bulk canopy resistance (rc) as a function of meteorological variables and then calculate the hourly evapotranspiration using the Penman–Monteith equation, so that traditional crop coefficients are not needed. As far as we know, there are no published studies regarding using this method for a maize crop. The objective of this study was to calibrate and validate the canopy resistance for an irrigated continuous maize crop in the Midwestern United States (US). In addition, we determined the effect of derivation year, bowen ratio, and the extent of canopy. In this study we derive empirical coefficients necessary to estimate rc for maize, five years (2001–2005) were considered. A split-sample approach was taken, in which each year’s data was taken as a potential calibration data set and validation was accomplished while using the other four years of data. We grouped the data by green leaf area index (GLAI) and the Bowen ratio (β) by parsing the data into a 3 × 3 grouping: LAI (≥2, ≥3, and ≥4) and |β| (≤0.1, ≤0.2, and ≤0.3). The best fit data indicated reasonably good results for all nine groupings, so that the calibration coefficients derived for the conditions LAI ≥ 2 and |β| ≤ 0.3 were taken in light of the longer span associated with LAI ≥ 2 and the larger number of hours. For the calibrations in this subgroup, the results indicate that the annual empirical coefficients for rc are nearly the same and equally effective, regardless of the year used for calibration. Our validation included all the daytime hours regardless of β. Thus, it was concluded that the calibration at our site was independent of the derivation year. Knowledge of the Bowen ratio was useful in calibration, but accurate ET estimates (validation) can be obtained without knowledge of the Bowen ratio. Validation resulted in hourly ET estimates for irrigated maize that explained 83% to 86% of the variation in measured ET with an accuracy of ± 0.2 mm.

Bio-Capture of Solid Pollutants by Vegetation Canopy Cave in Shallow Water Flow.

Vegetation has already been acknowledged to have the ability to remove fine solid pollutants by retention and absorption, and is widely used in the biorestoration engineering of natural shallow water flow. Vegetation usually takes a long time to obtain the expected removal rate. Therefore, vegetation is not applicable for some urgent or pressing situations. In addition, in traditional biorestoration engineering, solid pollutants usually deposit in the soil of flow bed, which infiltrates into the far-field and accumulates in crops to threaten human health. Herein, we propose a new biotechnique of foliage capture by designing a cave on the top of a vegetation canopy, which is aimed to enhance the removal efficiency (i.e., achieve quick removal) and avoid the soil deposition of pollutants. The effectiveness and efficiency of this new design were validated by a set of indoor water flume experiments, with one flat canopy top configuration serving as the model of a traditional bioretention system and three cave configurations of differing aspect ratios. The results showed that compared with that of the flat canopy top, the total amount of foliage-captured solid particles for the three caved canopies increased by 3.8, 7.3, and 12.2 times. Further, we found that the foliage-capture efficiency depended on the aspect ratio of the canopy cave. The results revealed that the effectiveness of foliage capture and the enhanced efficiency were mainly from three hydrodynamic mechanisms: (i) as flow penetrated the cave boundary from the above-canopy region to the within-canopy region, it entrained solid pollutants to collide with the foliage and increased their fate of capture; (ii) the large eddy vortices of turbulence broke due to the increasing canopy resistance, which resulted in enhanced mixing dynamics for fine, suspended, solid pollutants to collide into foliage; and (iii) the flow shear along the cave boundary decreased, which provided a reduced lift force for solid pollutants to suspend or resuspend. Comparisons between the flat canopy and caved canopies of three aspect ratios showed that the design of the canopy cave is highly significant for capture efficiency.

A three-source satellite algorithm for retrieving all-sky evapotranspiration rate using combined optical and microwave vegetation index at twenty AsiaFlux sites

Evapotranspiration (ET) composed of transpiration from vegetation (ETveg) and evaporation from soil (ETsoil) and interception water (ETint) is a crucial process for driving global water and energy cycle. In this study, a three-source satellite ET algorithm is developed for estimating instantaneous ET rate (ETcal) under clear and non-rainy cloudy sky conditions and is validated at 20 AsiaFlux sites of multiple vegetation types (evergreen and deciduous forests, croplands and grasslands) in East Asia. The ET algorithm is completely independent from ground-based measurements and thus has the potential to be used on regional scale. All-sky surface net radiation flux is derived from satellite products. Satellite optical Normalized Difference Vegetation Index (NDVI) is used to partition the surface available energy into vegetated area and bare soil area. Satellite microwave Emissivity Difference Vegetation Index (EDVI), an indicator of vegetation water content, is utilized to estimate canopy resistance and transpiration from vegetation. Evaporation components from canopy interception water and soil surface are estimated based on Priestley-Taylor method. The estimated evaporation fraction (EF) for all sites can produce a small absolute bias of less than 0.03 (or 8.1%) with a good determination coefficient (R2) larger than 0.42 when validated against the corrected in-situ measured EF on instantaneous and long-term mean scales. Instantaneous ETcal under all sky conditions are found to have a R2 of 0.61, a bias of 16.5 Wm-2 (13.7%) and a root mean square error (RMSE) of 63.6 Wm-2 (52.5%) over all sites, respectively. The performances of this algorithm are better achieved on 16-day (R2 = 0.66, RMSE = 44.1 Wm-2) and monthly (R2 = 0.70, RMSE = 39.1 Wm-2) scales. More importantly, EDVI-based ET method is able to produce ETcal with stable and good accuracy from clear sky to overcast sky (bias < 22 Wm-2 or 18%, RMSE < 77 Wm-2 or 59%). The daily ET and its components (ETveg, ETsoil and ETint) derived from our algorithm are further compared with those from Global Land Evaporation Amsterdam Model (GLEAM) ET products. EDVI-based ET (EDVI-ET) generally shows equal performances with GLEAM-ET when using in-situ ET as reference. EDVI-ETveg shows a fairly good correlation (R2 = 0.21) and an underestimation of -0.32 mm/day compared with GLEAM-ETveg. EDVI-ETint shows a significant correlation (R2 = 0.30) with GLEAM-ETveg after excluding three outlier tropical forest sites. Meanwhile, EDVI-ETsoil shows a fairly good positive correlation (R2 = 0.15) and an overestimation of 0.23 mm/day compared with GLEAM-ETsoil. The results indicate that our method has great potential for regional ET estimation under various cloud conditions when combined with satellite optical and microwave remote sensing.

Modeling evapotranspiration for cucumber plants based on the Shuttleworth-Wallace model in a Venlo-type greenhouse

Partitioning of evapotranspiration (ETc) into soil evaporation (Eg) and plants transpiration (Tr) is of great importance to assess biomass production and improve water use efficiency under greenhouse conditions. The Shuttleworth-Wallace (SW) model, which is used to separately predict Eg and Tr has been validated by many studies in open field, however, the model's parameters for the low wind speed and heterogeneous underlying surface in greenhouses are quite different from the open field. Therefore, an experiment was conducted in a Venlo-type greenhouse in south-east China during two planting seasons of cucumber plants in 2018, where the ETc and Tr were directly measured by lysimeters and sap flow sensors. The soil surface and canopy resistances were parameterized based on the soil water content at 5–10 cm depth and solar radiation inside the greenhouse, respectively. The SW model simulated ETc and Tr at hourly interval with root mean square error (RMSE) and index of agreement (d) of 42.10 W m−2 and 0.93; 40.50 W m−2 and 0.91 for the spring season, while for the autumn season the values were 26.60 W m−2 and 0.93; 15.63 W m−2 and 0.93, respectively. The average Eg / ETc were 7.75% and 21.87% for spring and autumn planting seasons, respectively, indicating that the Tr was the dominant component of ETc of cucumber grown in greenhouse over the full crop season. Our research shows the parameterized SW model would be a relatively accurate way to separately simulate the dynamic variations of the Tr and Eg, and for future use to improve irrigation scheduling for cucumber plants under greenhouse conditions.

Update and evaluation of the ozone dry deposition in Oslo CTM3 v1.0

Abstract. High concentrations of ozone in ambient air are hazardous not only to humans but to the ecosystem in general. The impact of ozone damage on vegetation and agricultural plants in combination with advancing climate change may affect food security in the future. While the future scenarios in themselves are uncertain, there are limiting factors constraining the accuracy of surface ozone modeling also at present: the distribution and amount of ozone precursors and ozone-depleting substances, the stratosphere–troposphere exchange, as well as scavenging processes. Removal of any substance through gravitational settling or by uptake by plants and soil is referred to as dry deposition. The process of dry deposition is important for predicting surface ozone concentrations and understanding the observed amount and increase of tropospheric background ozone. The conceptual dry deposition velocities are calculated following a resistance-analogous approach, wherein aerodynamic, quasi-laminar, and canopy resistance are key components, but these are hard to measure explicitly. We present an update of the dry deposition scheme implemented in Oslo CTM3. We change from a purely empirical dry deposition parameterization to a more process-based one which takes the state of the atmosphere and vegetation into account. We examine the sensitivity of the scheme to various parameters, e.g., the stomatal conductance-based description of the canopy resistance and the choice of ozone surface resistance, and evaluate the resulting modeled ozone dry deposition with respect to observations and multi-model studies. Individual dry deposition velocities are now available for each land surface type and agree generally well with observations. We also estimate the impact on the modeled ozone concentrations at the surface. We show that the global annual total ozone dry deposition decreases with respect to the previous model version (−37 %), leading to an increase in surface ozone of more than 100 % in some regions. While high sensitivity to changes in dry deposition to vegetation is found in the tropics and the Northern Hemisphere, the largest impact on global scales is associated with the choice of prescribed ozone surface resistance over the ocean and deserts.

A novel model of water-heat coupling for water-saving irrigated rice fields based on water and energy balance: Model formulation and verification

It is necessary to quantify the hydrothermal processes by develop a water-heat coupling model in rice fields where the transfer between water and energy is dramatically violent, under the circumstance that water-saving irrigation (WSI) was widely used in rice paddy due to the increasing water scarcity. Based on the theory of energy and water balance, considering the interaction of impedance near the ground, a simplified holistic recursive model of water-heat coupling was proposed in the soil–plant–atmosphere continuum (SPAC) system at hourly and daily scales, and the parameters were fitted based on water and energy balance components measured in WSI rice fields. The model, takes various soil moisture conditions into consideration, integrates all the terms in the surface energy balance and the water balance with conventional meteorological data as inputs. Additionally, the model accounts for the specific drying-wetting cycles condition for WSI rice field in the calculation of the canopy resistance (rc) and the recursive process. Variations in crop growth and meteorology were also considered. The results showed that the model performed well in simulating the water and heat fluxes, and temperature profiles during the growth of the rice. This is encouraging for modelling the response of hydrothermal process to drying-wetting cycles or irrigation regimes, which is help for improving the water use efficiency in rice field. Meanwhile, this study indicates that the systemic model is efficient and useful for a better understanding the interaction between hydrological and energy processes in the WSI rice ecosystem.