Simulation of the canopy resistance of Phragmites australis in Liaohe Delta wetland, northeastern China

Abstract Evapotranspiration (ET) is the major cause of wetland water loss. The Penman–Monteith model is the most suitable ET model for wetlands. However, its accuracy depends on canopy resistance. Here, we studied the Phragmites australis community in the Liaohe Delta, northeastern China. We used flux and environmental data from the Panjin Wetland Ecosystem Research Station, and physiological and ecological parameters. Canopy resistance was calculated by the Penman–Monteith model, and canopy resistance and its influencing factors were analyzed. We created a canopy resistance model, named the Phragmites australis wetland (PW) model, using leaf stomatal resistance, leaf area index (LAI) and environmental factors. The PW model differed from the traditional Jarvis model in that the effective LAI was added, and the stomatal resistance was changed from a fixed to dynamic value and the environmental factors only contained two items: solar radiation and water vapor pressure difference. The PW model allowed the conversion from leaf scale to canopy scale. A comparison of the PW model with the Jarvis model parameters showed that accuracy improved significantly: R2 values increased from 0.56 to 0.74. The model can provide parameters for P. australis ET models and provide a new method for accurate estimation of wetland ET.

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

Agronomy ◽

10.3390/agronomy10121985 ◽

2020 ◽

Vol 10 (12) ◽

pp. 1985

Author(s):

Georgios Nikolaou ◽

Damianos Neocleous ◽

Evangelini Kitta ◽

Nikolaos Katsoulas

Keyword(s):

Cooling System ◽

Ventilation System ◽

Energy Balance Equation ◽

Accurate Estimation ◽

Model Parameters ◽

Canopy Resistance ◽

Climate Control ◽

Evaporative Demand ◽

Air Ventilation ◽

Evaporative Cooling System

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.

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Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

Remote Sensing ◽

10.3390/rs13163069 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3069

Author(s):

Yadong Liu ◽

Junhwan Kim ◽

David H. Fleisher ◽

Kwang Soo Kim

Keyword(s):

Time Series ◽

Leaf Area Index ◽

Leaf Area ◽

Crop Yield ◽

Satellite Data ◽

Growing Season ◽

Environmental Data ◽

Area Index ◽

Current Season ◽

Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

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Generic Additive Allometric Models and Biomass Allocation for Two Natural Oak Species in Northeastern China

Forests ◽

10.3390/f12060715 ◽

2021 ◽

Vol 12 (6) ◽

pp. 715

Author(s):

Shengwang Meng ◽

Fan Yang ◽

Sheng Hu ◽

Haibin Wang ◽

Huimin Wang

Keyword(s):

Biomass Allocation ◽

Tree Height ◽

Northeastern China ◽

Seemingly Unrelated Regression ◽

Biomass Estimation ◽

Model Parameters ◽

Stem Biomass ◽

Crown Width ◽

Biomass Models ◽

Mongolian Oak

Current models for oak species could not accurately estimate biomass in northeastern China, since they are usually restricted to Mongolian oak (Quercus mongolica Fisch. ex Ledeb.) on local sites, and specifically, no biomass models are available for Liaodong oak (Quercuswutaishanica Mayr). The goal of this study was, therefore, to develop generic biomass models for both oak species on a large scale and evaluate the biomass allocation patterns within tree components. A total of 159 sample trees consisting of 120 Mongolian oak and 39 Liaodong oak were harvested and measured for wood (inside bark), bark, branch and foliage biomass. To account for the belowground biomass, 53 root systems were excavated following the aboveground harvest. The share of biomass allocated to different components was assessed by calculating the ratios. An aboveground additive system of biomass models and belowground equations were fitted based on predictors considering diameter (D), tree height (H), crown width (CW) and crown length (CL). Model parameters were estimated by jointly fitting the total and the components’ equations using the weighted nonlinear seemingly unrelated regression method. A leave-one-out cross-validation procedure was used to evaluate the predictive ability. The results revealed that stem biomass accounts for about two-thirds of the aboveground biomass. The ratio of wood biomass holds constant and that of branches increases with increasing D, H, CW and CL, while a reverse trend was found for bark and foliage. The root-to-shoot ratio nonlinearly decreased with D, ranging from 1.06 to 0.11. Tree diameter proved to be a good predictor, especially for root biomass. Tree height is more prominent than crown size for improving stem biomass models, yet it puts negative effects on crown biomass models with non-significant coefficients. Crown width could help improve the fitting results of the branch and foliage biomass models. We conclude that the selected generic biomass models for Mongolian oak and Liaodong oak will vigorously promote the accuracy of biomass estimation.

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Determination of Environmental Factors for the Implementation of the Exploitability Index in Industrial Aggregate Mining Using Multi-Criteria Analysis

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10040196 ◽

2021 ◽

Vol 10 (4) ◽

pp. 196

Author(s):

Julio Manuel de Luis-Ruiz ◽

Benito Ramiro Salas-Menocal ◽

Gema Fernández-Maroto ◽

Rubén Pérez-Álvarez ◽

Raúl Pereda-García

Keyword(s):

Environmental Factors ◽

Environmental Factor ◽

Human Life ◽

Accurate Estimation ◽

Analytic Hierarchy ◽

Main Components ◽

Hierarchy Process ◽

Made In

The quality of human life is linked to the exploitation of mining resources. The Exploitability Index (EI) assesses the actual possibilities to enable a mine according to several factors. The environment is one of the most constraining ones, but its analysis is made in a shallow way. This research is focused on its determination, according to a new preliminary methodology that sets the main components of the environmental impact related to the development of an exploitation of industrial minerals and its weighting according to the Analytic Hierarchy Process (AHP). It is applied to the case of the ophitic outcrops in Cantabria (Spain). Twelve components are proposed and weighted with the AHP and an algorithm that allows for assigning a normalized value for the environmental factor to each deposit. Geographic Information Systems (GISs) are applied, allowing us to map a large number of components of the environmental factors. This provides a much more accurate estimation of the environmental factor, with respect to reality, and improves the traditional methodology in a substantial way. It can be established as a methodology for mining spaces planning, but it is suitable for other contexts, and it raises developing the environmental analysis before selecting the outcrop to be exploited.

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The impact of environmental variables on the spread of COVID-19 in the Republic of Korea

Scientific Reports ◽

10.1038/s41598-021-85493-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yong Kwan Lim ◽

Oh Joo Kweon ◽

Hye Ryoun Kim ◽

Tae-Hyoung Kim ◽

Mi-Kyung Lee

Keyword(s):

Environmental Factors ◽

Virus Disease ◽

Environmental Parameters ◽

Environmental Data ◽

Republic Of Korea ◽

Metropolitan Region ◽

Health Concern ◽

Ozone Level ◽

The Republic ◽

The Impact

AbstractCorona virus disease 2019 (COVID-19) has been declared a global pandemic and is a major public health concern worldwide. In this study, we aimed to determine the role of environmental factors, such as climate and air pollutants, in the transmission of COVID-19 in the Republic of Korea. We collected epidemiological and environmental data from two regions of the Republic of Korea, namely Seoul metropolitan region (SMR) and Daegu-Gyeongbuk region (DGR) from February 2020 to July 2020. The data was then analyzed to identify correlations between each environmental factor with confirmed daily COVID-19 cases. Among the various environmental parameters, the duration of sunshine and ozone level were found to positively correlate with COVID-19 cases in both regions. However, the association of temperature variables with COVID-19 transmission revealed contradictory results when comparing the data from SMR and DGR. Moreover, statistical bias may have arisen due to an extensive epidemiological investigation and altered socio-behaviors that occurred in response to a COVID-19 outbreak. Nevertheless, our results suggest that various environmental factors may play a role in COVID-19 transmission.

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Adaptive State-of-Charge Estimation for Lithium-Ion Batteries by Considering Capacity Degradation

Electronics ◽

10.3390/electronics10020122 ◽

2021 ◽

Vol 10 (2) ◽

pp. 122

Author(s):

Peipei Xu ◽

Junqiu Li ◽

Chao Sun ◽

Guodong Yang ◽

Fengchun Sun

Keyword(s):

Equivalent Circuit Model ◽

Lithium Ion ◽

Maximum Error ◽

State Of Charge ◽

Recursive Least Squares ◽

Accurate Estimation ◽

Model Parameters ◽

Soc Estimation ◽

Capacity Degradation ◽

Battery Capacity

The accurate estimation of a lithium-ion battery’s state of charge (SOC) plays an important role in the operational safety and driving mileage improvement of electrical vehicles (EVs). The Adaptive Extended Kalman filter (AEKF) estimator is commonly used to estimate SOC; however, this method relies on the precise estimation of the battery’s model parameters and capacity. Furthermore, the actual capacity and battery parameters change in real time with the aging of the batteries. Therefore, to eliminate the influence of above-mentioned factors on SOC estimation, the main contributions of this paper are as follows: (1) the equivalent circuit model (ECM) is presented, and the parameter identification of ECM is performed by using the forgetting-factor recursive-least-squares (FFRLS) method; (2) the sensitivity of battery SOC estimation to capacity degradation is analyzed to prove the importance of considering capacity degradation in SOC estimation; and (3) the capacity degradation model is proposed to perform the battery capacity prediction online. Furthermore, an online adaptive SOC estimator based on capacity degradation is proposed to improve the robustness of the AEKF algorithm. Experimental results show that the maximum error of SOC estimation is less than 1.3%.

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Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage

Plant Methods ◽

10.1186/s13007-020-00693-3 ◽

2020 ◽

Vol 16 (1) ◽

Author(s):

Shanjun Luo ◽

Yingbin He ◽

Qian Li ◽

Weihua Jiao ◽

Yaqiu Zhu ◽

...

Keyword(s):

Precision Agriculture ◽

Growth Stage ◽

Estimation Error ◽

Potato Yield ◽

Hyperspectral Data ◽

Single Stage ◽

Accurate Estimation ◽

Yield Estimation ◽

Area Index ◽

Red Edge

Abstract Background The accurate estimation of potato yield at regional scales is crucial for food security, precision agriculture, and agricultural sustainable development. Methods In this study, we developed a new method using multi-period relative vegetation indices (rVIs) and relative leaf area index (rLAI) data to improve the accuracy of potato yield estimation based on the weighted growth stage. Two experiments of field and greenhouse (water and nitrogen fertilizer experiments) in 2018 were performed to obtain the spectra and LAI data of the whole growth stage of potato. Then the weighted growth stage was determined by three weighting methods (improved analytic hierarchy process method, IAHP; entropy weight method, EW; and optimal combination weighting method, OCW) and the Slogistic model. A comparison of the estimation performance of rVI-based and rLAI-based models with a single and weighted stage was completed. Results The results showed that among the six test rVIs, the relative red edge chlorophyll index (rCIred edge) was the optimal index of the single-stage estimation models with the correlation with potato yield. The most suitable single stage for potato yield estimation was the tuber expansion stage. For weighted growth stage models, the OCW-LAI model was determined as the best one to accurately predict the potato yield with an adjusted R2 value of 0.8333, and the estimation error about 8%. Conclusion This study emphasizes the importance of inconsistent contributions of multi-period or different types of data to the results when they are used together, and the weights need to be considered.

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Forest summer albedo is sensitive to species and thinning: how should we account for this in Earth system models?

Biogeosciences ◽

10.5194/bg-11-2411-2014 ◽

2014 ◽

Vol 11 (8) ◽

pp. 2411-2427 ◽

Cited By ~ 19

Author(s):

J. Otto ◽

D. Berveiller ◽

F.-M. Bréon ◽

N. Delpierre ◽

G. Geppert ◽

...

Keyword(s):

Forest Management ◽

Tree Species ◽

Near Infrared ◽

Model Parameters ◽

Earth System ◽

Forest Thinning ◽

Area Index ◽

System Models ◽

Maximum Change ◽

Earth System Models

Abstract. Although forest management is one of the instruments proposed to mitigate climate change, the relationship between forest management and canopy albedo has been ignored so far by climate models. Here we develop an approach that could be implemented in Earth system models. A stand-level forest gap model is combined with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning on summertime canopy albedo. This approach reveals which parameter has the largest affect on summer canopy albedo: we examined the effects of three forest species (pine, beech, oak) and four thinning strategies with a constant forest floor albedo (light to intense thinning regimes) and five different solar zenith angles at five different sites (40° N 9° E–60° N 9° E). During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning. These trends continue until the end of the rotation, where thinning explains up to 50% of the variance in near-infrared albedo and up to 70% of the variance in visible canopy albedo. The absolute summertime canopy albedo of all species ranges from 0.03 to 0.06 (visible) and 0.20 to 0.28 (near-infrared); thus the albedo needs to be parameterised at species level. In addition, Earth system models need to account for forest management in such a way that structural changes in the canopy are described by changes in leaf area index and crown volume (maximum change of 0.02 visible and 0.05 near-infrared albedo) and that the expression of albedo depends on the solar zenith angle (maximum change of 0.02 visible and 0.05 near-infrared albedo). Earth system models taking into account these parameters would not only be able to examine the spatial effects of forest management but also the total effects of forest management on climate.

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Disentangling the response of forest and grassland energy exchange to heatwaves under idealized land–atmosphere coupling

Biogeosciences Discussions ◽

10.5194/bgd-11-5969-2014 ◽

2014 ◽

Vol 11 (4) ◽

pp. 5969-5995

Author(s):

C. C. van Heerwaarden ◽

A. J. Teuling

Keyword(s):

Heat Wave ◽

Heat Waves ◽

Dynamic Properties ◽

Sensible Heat Flux ◽

Early Morning ◽

Stomatal Resistance ◽

Heat Fluxes ◽

Sensible Heat ◽

Area Index ◽

Wave Conditions

Abstract. This study investigates the difference in land–atmosphere interactions between grassland and forest during typical heat wave conditions in order to understand the controversial results of Teuling et al. (2010) (T10, hereafter), who have found the systematic occurrence of higher sensible heat fluxes over forest than over grassland during heat wave conditions. With a simple, but accurate coupled land–atmosphere model, we are able to reproduce the findings of T10 for both normal summer and heat wave conditions, and to carefully explore the sensitivity of the coupled land–atmosphere system to changes in incoming radiation and early-morning temperature. Our results emphasize the importance of fast processes during the onset of heat waves, since we are able to explain the results of T10 without having to take into account changes in soil moisture. In order to disentangle the contribution of differences in several static and dynamic properties between forest and grassland, we have performed an experiment in which new land use types are created that are equal to grassland, but with one of its properties replaced by that of forest. From these, we conclude that the closure of stomata in the presence of dry air is by far the most important process in creating the different behavior of grassland and forest during the onset of a heat wave. However, we conclude that for a full explanation of the results of T10 also the other properties (albedo, roughness and the ratio of minimum stomatal resistance to leaf-area index) play an important, but indirect role; their influences mainly consist of strengthening the feedback that leads to the closure of the stomata by providing more energy that can be converted into sensible heat. The model experiment also confirms that, in line with the larger sensible heat flux, higher atmospheric temperatures occur over forest.

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Impactos das mudanças climáticas na demanda hídrica e duração do ciclo do sorgo forrageiro e feijão-caupi no estado de Pernambuco

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v8.0.p542-559 ◽

2015 ◽

Vol 8 ◽

pp. 542

Author(s):

José Edson Florentino de Morais ◽

Thieres George Freire da Silva ◽

Marcela Lúcia Barbosa ◽

Wellington Jairo da Silva Diniz ◽

Carlos André Alves de Souza ◽

...

Keyword(s):

Climate Change ◽

Relative Humidity ◽

Air Temperature ◽

Water Demand ◽

Stomatal Resistance ◽

The State ◽

Extreme Weather Events ◽

Climate Change Scenarios ◽

Area Index ◽

Forage Sorghum

O aumento na ocorrência de eventos climáticos extremos nas últimas décadas é uma forte evidência das mudanças climáticas. Em regiões Semiáridas, onde a pressão de desertificação tem se intensificado, são esperadas diminuição da disponibilidade de água e maior ocorrência de períodos seca, e, consequentemente, efeitos na resposta fisiológica das plantas. Assim, objetivou-se analisar os impactos dos cenários de mudanças climáticas sobre a duração do ciclo fenológico e a demanda de água do sorgo forrageiro e do feijão-caupi cultivados no Estado de Pernambuco. Foram utilizados os valores mensais da normal climatológica brilho solar, temperatura do ar, umidade relativa do ar e velocidade do vento de dez municípios. Considerou-se um aumento de 1,8°C (Cenário B2) e 4,0°C (Cenário A1F1) na temperatura do ar e um decréscimo de 5,0% dos valores absolutos de umidade relativa do ar, além do aumento de 22% na resistência estomática e de 4% no índice de área foliar. Com base nessas informações foram gerados três cenários: situação atual e projeções futuras para B2 e A1F1. Os resultados revelaram uma redução média de 11% (B2) e 20% (A1F1), e de 10% (B2) e 17% (A1F1) na duração do ciclo, e de 4% (B2) e 8% (A1F1), e 2% (B2) e 5% (A1F1) na demanda de água acumulada para o sorgo forrageiro e feijão-caupi, respectivamente. Conclui-se que a magnitude das reduções da duração do ciclo e a demanda de água simulada para as culturas do sorgo forrageiro e do feijão-caupi variaram espaço-temporalmente no Estado de Pernambuco com os cenários de mudanças climáticas.ABSTRACT The increase in the occurrence of extreme weather events in recent decades is a strong evidence of climate change. In semiarid regions, where the pressure of desertification has intensified, are expected to decrease in the availability of water and higher occurrence of drought periods, and, consequently, effects on physiological response of plants. Thus, the objective of analyzing the impacts of climate change scenarios on the duration of phenological cycle and water demand of forage sorghum and cowpea, grown in the State of Pernambuco. Monthly values were used normal climatological solar brightness, air temperature, relative humidity and wind speed of ten municipalities. It was considered an increase of 1.8° C (B2 Scenario) and 4.0° C (A1F1 Scenario) on air temperature and a decrease of 5.0% of the absolute values of relative humidity, in addition to the 22% increase in stomatal resistance and 4% in leaf area index. Based on this information were generated three scenarios: current situation and future projections for B2, A1F1. The results revealed an average reduction of 11% (B2) and 20% (A1F1), and 10% (B2) and 17% (A1F1) for the duration of the cycle, and 4% (B2) and 8% (A1F1), and 2% (B2) and 5% (A1F1) in accumulated water demand for forage sorghum and cowpea, respectively. It is concluded that the magnitude of the reductions in the duration of the cycle and the simulated water demand for crops of forage sorghum and cowpea ranged space-temporarily in the State of Pernambuco with climate change scenarios.

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