Soil water forecasting in the continental United States: relative forcing by meteorology versus leaf area index and the effects of meteorological forecast errors

2004 ◽  
Vol 30 (5) ◽  
pp. 717-730 ◽  
Author(s):  
Michael A White ◽  
Ramakrishna R Nemani
1992 ◽  
Vol 43 (7) ◽  
pp. 1527 ◽  
Author(s):  
PS Carberry ◽  
RC Muchow

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.


2014 ◽  
Vol 522-524 ◽  
pp. 699-708 ◽  
Author(s):  
Xiang Hui Lu ◽  
Hua Bai ◽  
Hui Ying Liu

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.


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 ◽  
...  

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.


Author(s):  
Patrícia S. de S. Gondim ◽  
José R. de S. Lima ◽  
Antonio C. D. Antonino ◽  
Claude Hammecker ◽  
Renan A. B. da Silva ◽  
...  

A micrometeorological experiment was conducted over grasslands in a semi-arid region of north-eastern Brazil (São João, Pernambuco) from January to December 2011, using the Bowen ratio energy balance method, to improve the current understanding of energy partitioning and water vapour exchange over this ecosystem in this region. The objectives of the present study were to quantify the seasonal and diurnal variations in energy and water vapour exchanges over grasslands and understand the biotic and abiotic factors controlling the energy partitioning of this ecosystem. In the dry period, the low stored soil water limited the grass production and leaf area index, and as a consequence of these conditions, most of the annual net radiation (58%) was consumed in sensible heat flux. During the course of the study the evaporative fraction was linearly related to the leaf area index. The total annual evapotranspiration and its daily maximum were 543.8 mm and 3.14 mm d-1. The seasonal and diurnal variations in energy partitioning and evapotranspiration were controlled by soil water availability and leaf area index.


2019 ◽  
Vol 20 (7) ◽  
pp. 1359-1377 ◽  
Author(s):  
Sujay V. Kumar ◽  
David M. Mocko ◽  
Shugong Wang ◽  
Christa D. Peters-Lidard ◽  
Jordan Borak

Abstract Accurate representation of vegetation states is required for the modeling of terrestrial water–energy–carbon exchanges and the characterization of the impacts of natural and anthropogenic vegetation changes on the land surface. This study presents a comprehensive evaluation of the impact of assimilating remote sensing–based leaf area index (LAI) retrievals over the continental United States in the Noah-MP land surface model, during a time period of 2000–17. The results demonstrate that the assimilation has a beneficial impact on the simulation of key water budget terms, such as soil moisture, evapotranspiration, snow depth, terrestrial water storage, and streamflow, when compared with a large suite of reference datasets. In addition, the assimilation of LAI is also found to improve the carbon fluxes of gross primary production (GPP) and net ecosystem exchange (NEE). Most prominent improvements in the water and carbon variables are observed over the agricultural areas of the United States, where assimilation improves the representation of vegetation seasonality impacted by cropping schedules. The systematic, added improvements from assimilation in a configuration that employs high-quality boundary conditions highlight the significant utility of LAI data assimilation in capturing the impacts of vegetation changes.


2018 ◽  
Author(s):  
Qinchuan Xin ◽  
Yongjiu Dai ◽  
Xiaoping Liu

Abstract. Terrestrial plants play a key role in regulating the exchange of energy and materials between the land surface and the atmosphere. Robust terrestrial biosphere models that simulate both time series of leaf dynamics and canopy photosynthesis are required to understand the vegetation-climate interactions. This study proposes a time stepping scheme to simulate leaf area index (LAI), phenology, and gross primary production (GPP) simultaneously via only climate variables based on an ecological assumption that plants allocate leaf biomass till an environment could sustain to maximize photosynthetic reproduction. The method establishes a linear function between the steady-state LAI and the corresponding GPP, which is used to track the suitability of environmental conditions for plant photosynthesis, and applies the MOD17 algorithm to form simultaneous equations together, which can be solved numerically. To account for the time lag in plant responses of leaf allocation to environment variation, a time stepping scheme is developed to simulate the LAI time series based on the solved steady-state LAI. The simulated LAI time series is then used to derive the timing of key phenophases and simulate canopy GPP with the MOD17 algorithm. The developed method is applied to deciduous broadleaf forests in eastern United States and has found to perform well on simulating canopy LAI and GPP at the site scale as evaluated using both flux tower and satellite data. The method could also capture the spatiotemporal variation of vegetation LAI and phenology across eastern United States as compared with satellite observations. The developed time-stepping scheme provides a simplified and improved version of our previous modeling approach and forms a potential basis for regional to global applications in future studies.


1997 ◽  
Vol 24 (6) ◽  
pp. 831 ◽  
Author(s):  
Michael Battaglia ◽  
Peter Sands

A simple model, PROMOD, predicts the growth of a forest following canopy closure, i.e. under conditions in which the foliage biomass has attained a steady state. The principal output from PROMOD is peak mean annual increment. However, additional output available includes the closed-canopy leaf area index, evapotranspiration and water use efficiency. In addition, an indication of biomass partitioning around the time of peak MAI and the relative effects different environmental factors play in limiting production can be obtained. PROMOD is based on a generalisation of a simple forest growth model which predicts biomass production and partitioning at the stand level with a daily or annual time step. The minimum level of inputs required by PROMOD are of a quality and quantity that forest managers can readily and cheaply obtain for screening prospective plantation sites: the latitude, longitude, altitude, slope and aspect of the site and a classification of the soil depth, texture, stoniness, drainage and a rating of site fertility. However, PROMOD can be run using daily inputs of weather data and hence predict the seasonal variation of production. The closed-canopy leaf area index is calculated from the mean annual rainfall and temperature at the site, and a simple rating of site fertility. Annual production is calculated as the sum of daily production and takes diurnal temperature variation and possible seasonal photosynthetic acclimation into account. A simple soil water balance model is included in which water use is based on a crop factor which is a function of soil water content and a water use efficiency which is a function of vapour pressure deficit. The model was developed on the basis of data from nine plots of Eucalyptus globulus in south-eastern Tasmania and in Western Australia, and was validated using data from 19 plots in northern Tasmania.


2016 ◽  
Vol 13 (1) ◽  
pp. 239-252 ◽  
Author(s):  
H. Tang ◽  
S. Ganguly ◽  
G. Zhang ◽  
M. A. Hofton ◽  
R. F. Nelson ◽  
...  

Abstract. Leaf area index (LAI) and vertical foliage profile (VFP) are among the important canopy structural variables. Recent advances in lidar remote sensing technology have demonstrated the capability of accurately mapping LAI and VFP over large areas. The primary objective of this study was to derive and validate a LAI and VFP product over the contiguous United States (CONUS) using spaceborne waveform lidar data. This product was derived at the footprint level from the Geoscience Laser Altimeter System (GLAS) using a biophysical model. We validated GLAS-derived LAI and VFP across major forest biomes using airborne waveform lidar. The comparison results showed that GLAS retrievals of total LAI were generally accurate with little bias (r2 =  0.67, bias  =  −0.13, RMSE  =  0.75). The derivations of GLAS retrievals of VFP within layers were not as accurate overall (r2 =  0.36, bias  =  −0.04, RMSE  =  0.26), and these varied as a function of height, increasing from understory to overstory – 0 to 5 m layer: r2 =  0.04, bias  =  0.09, RMSE  =  0.31; 10 to 15 m layer: r2 =  0.53, bias  =  −0.08, RMSE  =  0.22; and 15 to 20 m layer: r2 =  0.66, bias  =  −0.05, RMSE  =  0.20. Significant relationships were also found between GLAS LAI products and different environmental factors, in particular elevation and annual precipitation. In summary, our results provide a unique insight into vertical canopy structure distribution across North American ecosystems. This data set is a first step towards a baseline of canopy structure needed for evaluating climate and land use induced forest changes at the continental scale in the future, and should help deepen our understanding of the role of vertical canopy structure in terrestrial ecosystem processes across varying scales.


1978 ◽  
Vol 70 (6) ◽  
pp. 912-917 ◽  
Author(s):  
S. Al‐Khafaf ◽  
P. J. Wierenga ◽  
B. C. Williams

Sign in / Sign up

Export Citation Format

Share Document