scholarly journals A generic model of forest canopy conductance dependent on climate, soil water availability and leaf area index

2000 ◽  
Vol 57 (8) ◽  
pp. 755-765 ◽  
Author(s):  
Andr� Granier ◽  
Denis Loustau ◽  
Nathalie Br�da
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Water Availability ◽  
Forest Canopy ◽  
Soil Water Availability ◽  
Generic Model ◽  
Canopy Conductance ◽  
Area Index

scholarly journals UAV Based Estimation of Forest Leaf Area Index (LAI) through Oblique Photogrammetry

2021 ◽  
Vol 13 (4) ◽  
pp. 803
Author(s):  
Lingchen Lin ◽  
Kunyong Yu ◽  
Xiong Yao ◽  
Yangbo Deng ◽  
Zhenbang Hao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Point Cloud ◽  
Forest Canopy ◽  
Estimation Method ◽  
Vertical Direction ◽  
Estimation Accuracy ◽  
3D Point Cloud ◽  
Area Index ◽  
Better Than

As a key canopy structure parameter, the estimation method of the Leaf Area Index (LAI) has always attracted attention. To explore a potential method to estimate forest LAI from 3D point cloud at low cost, we took photos from different angles of the drone and set five schemes (O (0°), T15 (15°), T30 (30°), OT15 (0° and 15°) and OT30 (0° and 30°)), which were used to reconstruct 3D point cloud of forest canopy based on photogrammetry. Subsequently, the LAI values and the leaf area distribution in the vertical direction derived from five schemes were calculated based on the voxelized model. Our results show that the serious lack of leaf area in the middle and lower layers determines that the LAI estimate of O is inaccurate. For oblique photogrammetry, schemes with 30° photos always provided better LAI estimates than schemes with 15° photos (T30 better than T15, OT30 better than OT15), mainly reflected in the lower part of the canopy, which is particularly obvious in low-LAI areas. The overall structure of the single-tilt angle scheme (T15, T30) was relatively complete, but the rough point cloud details could not reflect the actual situation of LAI well. Multi-angle schemes (OT15, OT30) provided excellent leaf area estimation (OT15: R2 = 0.8225, RMSE = 0.3334 m2/m2; OT30: R2 = 0.9119, RMSE = 0.1790 m2/m2). OT30 provided the best LAI estimation accuracy at a sub-voxel size of 0.09 m and the best checkpoint accuracy (OT30: RMSE [H] = 0.2917 m, RMSE [V] = 0.1797 m). The results highlight that coupling oblique photography and nadiral photography can be an effective solution to estimate forest LAI.

scholarly journals A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area Index

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 252
Author(s):  
Muhammad Shahinur Alam ◽  
David William Lamb ◽  
Nigel W. M. Warwick
Keyword(s):  
Stomatal Conductance ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Festuca Arundinacea ◽  
Radiation Energy ◽  
Scaling Up ◽  
Controlled Environment ◽  
Canopy Conductance ◽  
Individual Layer ◽  
Area Index

Estimating transpiration as an individual component of canopy evapotranspiration using a theoretical approach is extremely useful as it eliminates the complexity involved in partitioning evapotranspiration. A model to predict transpiration based on radiation intercepted at various levels of canopy leaf area index (LAI) was developed in a controlled environment using a pasture species, tall fescue (Festuca arundinacea var. Demeter). The canopy was assumed to be a composite of two indistinct layers defined as sunlit and shaded; the proportion of which was calculated by utilizing a weighted model (W model). The radiation energy utilized by each layer was calculated from the PAR at the top of the canopy and the fraction of absorbed photosynthetically active radiation (fAPAR) corresponding to the LAI of the sunlit and shaded layers. A relationship between LAI and fAPAR was also established for this specific canopy to aid the calculation of energy interception. Canopy conductance was estimated from scaling up of stomatal conductance measured at the individual leaf level. Other environmental factors that drive transpiration were monitored accordingly for each individual layer. The Penman–Monteith and Jarvis evapotranspiration models were used as the basis to construct a modified transpiration model suitable for controlled environment conditions. Specially, constructed self-watering tubs were used to measure actual transpiration to validate the model output. The model provided good agreement of measured transpiration (actual transpiration = 0.96 × calculated transpiration, R2 = 0.98; p < 0.001) with the predicted values. This was particularly so at lower LAIs. Probable reasons for the discrepancy at higher LAI are explained. Both the predicted and experimental transpiration varied from 0.21 to 0.56 mm h−1 for the range of available LAIs. The physical proportion of the shaded layer exceeded that of the sunlit layer near LAI of 3.0, however, the contribution of the sunlit layer to the total transpiration remains higher throughout the entire growing season.

The Impact of Noah-MP Physical Parameterizations on Modeling Water Availability during Droughts in the Texas-Gulf Region

2021 ◽  
Author(s):  
Wen-Ying Wu ◽  
Zong-Liang Yang ◽  
Michael Barlage
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Water Availability ◽  
Water Storage ◽  
Rooting Depth ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Area Index ◽  
Terrestrial Water ◽  
The Impact

AbstractTexas is subject to severe droughts, including the record-breaking one in 2011. To investigate the critical hydrometeorological processes during drought, we use a land surface model, Noah-MP, to simulate water availability and investigate the causes of the record drought. We conduct a series of experiments with runoff schemes, vegetation phenology, and plant rooting depth. Observation-based terrestrial water storage, evapotranspiration, runoff, and leaf area index are used to compare with results from the model. Overall, the results suggest that using different parameterizations can influence the modeled water availability, especially during drought. The drought-induced vegetation responses not only interact with water availability but also affect the ground temperature. Our evaluation shows that Noah-MP with a groundwater scheme produces a better temporal relationship in terrestrial water storage compared with observations. Leaf area index from dynamic vegetation is better simulated in wet years than dry years. Reduction of positive biases in runoff and reduction of negative biases in evapotranspiration are found in simulations with groundwater, dynamic vegetation, and deeper rooting zone depth. Multi-parameterization experiments show the uncertainties of drought monitoring and provide a mechanistic understanding of disparities in dry anomalies.

A simulation model of kenaf for assisting fibre industry planning in northern Australia. III. Model description and validation

1992 ◽  
Vol 43 (7) ◽  
pp. 1527 ◽  
Author(s):  
PS Carberry ◽  
RC Muchow
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Leaf Growth ◽  
Biomass Accumulation ◽  
Fibre Industry ◽  
Model Description ◽  
Northern Australia ◽  
Area Index ◽  
Extractable Soil

NTKENAF (Version 1.1) is a computer model which simulates the growth of kenaf (Hibiscus cannabinus L.) under rainfed conditions in tropical Australia. In daily time-steps, the model simulates the phenology, leaf area development, biomass accumulation and partitioning, soil water balance and dry matter yields of kenaf plants based on climatic and management inputs. The model assumes adequate nutrition and no effect of pests and diseases. The model uses daily maximum and minimum temperature, solar radiation and rainfall. The duration from sowing to flowering is predicted using temperature and photoperiod. Leaf growth is described as a function of node production (as determined by temperature), leaf area per node and leaf area senescence. Potential daily biomass is predicted from leaf area index, the light extinction coefficient and radiation use efficiency, and partitioned to the economic stem yield. Soil evaporation is predicted using a two-stage evaporation model, and plant transpiration is predicted from the daily biomass accumulation, a transpiration efficiency coefficient and predicted daily vapour pressure deficit. Plant extractable soil water is dependent on the available soil water range for each depth increment, the extraction front velocity, and the extent of water extraction at each depth. Daily transpiration and leaf growth are decreased below potential values once the fraction of available soil water declines below a threshold value. NTKENAF V1.1 has been validated against observed data from kenaf experiments conducted at two sites (lat. 13�48'S. and 14�28'S.) in northern Australia. The predictive accuracy of the model was good over a range in above-ground biomass up to 25 000 kg ha-1 (n = 40, r2 = 0.94, root mean square deviation = 1716 kg ha-1). Validations were also undertaken for predictions of the core and bark stem components, leaf area index and plant extractable soil water contents. The development of NTKENAF has provided a tool which can greatly aid assessment of the feasibility of a fibre industry based on kenaf in northern Australia.

Validate the DSSAT Model on Winter Wheat under Conservation Tillage Treatments in the West Henan, China

2014 ◽  
Vol 522-524 ◽  
pp. 699-708 ◽  
Author(s):  
Xiang Hui Lu ◽  
Hua Bai ◽  
Hui Ying Liu
Keyword(s):  
Water Balance ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Conservation Agriculture ◽  
Soil Water Balance ◽  
The West ◽  
Area Index ◽  
Straw Mulching

Crop growth simulation models can be useful in evaluating the impacts of different tillage and residue management operations on the changes in land productivity and soil-water balance components. They offer a potentially valuable set of tools for examining questions related to performance of conservation agriculture. This can be both to improve our understanding or conceptualization of processes and to improve quantitative predictions for use by agronomists, growers, policy makers or others. We applied the new Decision Support System for Agro-technology Transfer (DSSAT) version 4.5, an improved crop growth simulation model, to three conservation agriculture treatments and one conventional tillage treatment data from a field-scale study in west Henan region of China to predict winter-wheat yield, leaf area index and soil-water balance. The sites average annual precipitation is 632mm and it had a winter wheat-fallow-winter wheat rotation. There winter wheat planting in October and harvesting in next year June. The model was calibrated using 2005-2006 winter-wheat crop data from field experiments of the four treatments. The treatments were: (1) decreased tillage (DT): mulching of 10-15cm height straw and one ploughing operation to 25cm depth on July 1st; (2) zero tillage (ZT): zero tillage with 35-40cm height straw mulching; (3) subsoiling (SS): 35-40cm height straw mulching and subsoil to 40cm depth on July 1st; (4) conventional tillage (CT): 10-15cm height straw mulching and two ploughing operations 20cm deep on July 1st and October 1st. The DSSAT satisfactorily simulated the four treatments variations in winter-wheat yield, leaf area index and soil-water balance. There was better agreement between observed and predicted yields (the error absolute values were less than 3.95% and the error mean absolute values were less than 2.78%). The mean value of root mean square errors (RMSE) for simulated leaf area index (LAI) and soil water storage were 0.41cm2·cm-2 and 0.08cm3·cm-3 for DT, ZT, SS and CT, treatment respectively. The predicted water use efficiency for the four treatments were 15.85, 15.40, 16.58 and 15.81kg·mm-1·ha-1, respectively. These values were close to the values calculated from field measured data (16.82, 14.44, 16.86 and 15.66kg·mm-1·ha-1, respectively). Although the analysis results show us that the DSSAT V4.5 is well suited for simulating winter-wheat growth in the West Henan region of China, these results are preliminary and based on only one year of experimental data and four treatments and further long-term analyses need to be carried out for improving the understanding of the conservation agriculture cropping systems in the west Henan region of China.

scholarly journals Onset Date of Forest Canopy Detected from MODIS Leaf Area Index

2008 ◽  
Vol 31 (2) ◽  
pp. 153-159 ◽  
Author(s):  
So-Hee Kim ◽  
Sin-Kyu Kang ◽  
Jong-Hwan Lim
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Forest Canopy ◽  
Onset Date ◽  
Area Index

scholarly journals DIEBACK, LEAF AREA INDEX AND YIELD OF YOUNG EUCALYPT CLONES PLANTATION IN THE BRAZILIAN SAVANNAH REGION

2018 ◽  
Vol 41 (3) ◽  
Author(s):  
Geraldo Gonçalves dos Reis ◽  
Frederico de Freitas Alves ◽  
Maria das Graças Ferreira Reis ◽  
Felippe Coelho de Souza ◽  
Diogo Sena Baiero ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Water Deficit ◽  
Tree Height ◽  
Low Fertility ◽  
Limiting Factor ◽  
Soil Water Deficit ◽  
Area Index ◽  
Brazilian Savannah

ABSTRACT Eucalypt has been widely planted in Brazil, in the savannah region, which is characterized by high soil water deficit and low fertility. Dieback, leaf area index (LAI) and yield of young stands of 16 eucalypt clones were studied in Vazante, MG, Brazil (17º36’09"S and 46º 42’02"W). It was determined for each clone: a) the proportion of the tree height with dieback symptoms in the apical terminal (HWD%) and the proportion of trees with dieback (NWD%), at 13 months (end of the first dry season); b) the LAI at 13 and 21 months, and c) the yield at the age of 13, 19 and 25 months. HWD% reached 5-9%, and NWD%, 50-80%, for the five most susceptible clones, when the soil water deficit reached 508 mm in the year. LAI varied from 0.61 to 1.56, at 13 months, and from 2.31 to 3.48 at 21 months, presenting inverse relationship with dieback. The least susceptible clones to dieback achieved the highest yield up to 25 months of age. There was interaction between dieback and fertilizer levels only for three clones. There was a positive correlation (p < 0.001) between the LAI at the age of 13 months and the periodic monthly increment from 0 to 11 months, and from 11 to 19 months. The difference in dieback susceptibility among clones allows the selection of genotypes for regions where the soil water deficit is a major limiting factor.

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