Monitoring seasonal and phenological variability of cover management factor for wheat cropping systems under semi-arid climate conditions

Akgöz, Reşat; Saygın, Selen Deviren; Erpul, Günay; Tel, Selda

doi:10.1007/s10661-022-10064-1

Cited by 3 publications

(1 citation statement)

References 34 publications

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“…The model contains the effects of different influencing factors such as rainfall, topography, soil properties, vegetation cover or the type of tillage applied. Therefore, this method is suitable for investigating the effects of different vegetation cover or the variation in vegetation during the year [46,[48][49][50][51].…”

Section: Discussionmentioning

confidence: 99%

Spatial Modelling of Vineyard Erosion in the Neszmély Wine Region, Hungary Using Proximal Sensing

2022

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Intense soil erosion in the northern part of the Gerecse Hills, Hungary, is causing significant damage to vineyards in the area. Three vineyards in the Neszmély Wine Region were investigated to quantify the amount of eroded soils. The method was based on monitoring vineyards for one-year between July 2019 and June 2020. Every season, a set of photographs of the vineyards were taken from an unmanned aerial vehicle. The images were processed in a photogrammetric workflow to produce high-resolution digital terrain models (DTMs) and orthophotos, which were used to estimate the soil loss using the Universal Soil Loss Equation (USLE) model. Particular attention was paid to the effect of seasonal variation in vegetation cover and rainfall, and the erosion control effect of the inter-row grassing already applied in the vineyards was also modelled. The results confirm and quantify the extent to which intense summer rainfall has a more significant effect on erosion compared to autumn or winter rainfall.

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Section: Discussionmentioning

confidence: 99%

Spatial Modelling of Vineyard Erosion in the Neszmély Wine Region, Hungary Using Proximal Sensing

2022

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Useful indicators and models for assessing erosion control ecosystem service in a semi-arid forest landscape

Vatandaşlar

Yavuz

2022

Environ Monit Assess

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New values of the accumulated development rate for detailed the spring wheat phenological stage model calibrated with multilocal and multiyear documentation in subtropical Brazil

Barbosa,

Kochinski,

Fogaça

et al. 2023

Preprint

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The model for simulating wheat phenological development proposed by Wang and Engel (WE) represents a major advance in establishing wheat phenological phases based on air temperature and photoperiod information. However, the WE model was developed for winter wheat and may have flaws in the phenological prediction of spring wheat. In this sense, the study aims to predict in detail the phenological stages of spring wheat, with new values of the accumulated development rate and with no effect of vernalization (f(V) = 1.0) cultivated in the subtropical region from Brazil. Climatic and phenological information of three genotypes were collected at five locations and eleven sowing dates for calibration and validation of the WE model adjusted for spring wheat. The WE model multilocal and multiyear documentation of spring wheat growth were partitioned in El Niño, La Niña, and neutral conditions to calibrate and validate the model in five sites for five growing seasons. The original model was improved from three phenological events to ten phenological stages and the model coefficient was calibrated to predict the Julian date of occurrence of each stage. A validation dataset that contained 344 observations in different weather conditions was compared with the model outputs and it resulted in R2 and Willmott agreement index greater than 0.98, and a root mean square error (RMSE) of 4 days. The new values of the accumulated development rate predicted the dates of the developmental stage for spring wheat more precisely and with a low RMSE. The cumulative RMSE of the model along the growth period reached 6 days. The present model is a sharp tool to schedule spring wheat management.

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Monitoring seasonal and phenological variability of cover management factor for wheat cropping systems under semi-arid climate conditions

Cited by 3 publications

References 34 publications

Spatial Modelling of Vineyard Erosion in the Neszmély Wine Region, Hungary Using Proximal Sensing

Spatial Modelling of Vineyard Erosion in the Neszmély Wine Region, Hungary Using Proximal Sensing

Useful indicators and models for assessing erosion control ecosystem service in a semi-arid forest landscape

New values of the accumulated development rate for detailed the spring wheat phenological stage model calibrated with multilocal and multiyear documentation in subtropical Brazil

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