Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events

Valipour, Mohammad; Sefidkouhi, Mohammad Ali Gholami; Raeini−Sarjaz, Mahmoud

doi:10.1016/j.agwat.2016.08.025

Cited by 238 publications

(67 citation statements)

References 40 publications

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“…Similar models were also applied in predicting rainfall on agricultural areas taking into account many factors (Valipour 2016b). A modeling on the basis of autoregressive analysis was conducted during potential evapotranspiration determination including climate changes as well as extreme events in the past (Valipour et al 2017). …”

Section: Introductionmentioning

confidence: 99%

Influence of Contact Surface Type on the Mechanical Damages of Apples Under Impact Loads

Komarnicki

Stopa

Szyjewicz

et al. 2017

Food Bioprocess Technol

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This paper presents an analysis of mechanical damage carried out on 'Golden Delicious' apple variety, which was subjected to impact loads during free drop against various rigid plates. For this purpose, an analysis of the contact pressure based on determined contours and surface pressure distributions at the contact point between the fruit dropped from various heights against fixed hard plates was performed. The impact test was conducted by means of Tekscan® system supported by computer verifying analysis. To obtain impact loads as well as their courses, the surface pressures and the bruise volumes were determined. Furthermore, use of ultrathin pressure sensors allowed for determination of the characteristic shape of contact area and the impact of fruit onto rigid plate. The results showed that the impact of fruit against rigid surface (concrete, wood) generates high values of maximum surface pressure and the bruise volume, observed at dropping from 10 mm. A decrease in hardness of the test material (polyethylene foam) with decreasing maximum surface pressure approximately twice was noticed. The polyethylene foam is one of the best materials which protect fruit from mechanical damage, confirmed by the relation of bruise surface to contact surface, which did not exceed 35% during the impact at 150 mm. The results of proposed studies can contribute to developing of harvest, handling, and transport processes, aiming at reduction in losses among fruit growers and production costs, i.e., by improvement of transport method.

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Section: Introductionmentioning

confidence: 99%

Influence of Contact Surface Type on the Mechanical Damages of Apples Under Impact Loads

Komarnicki

Stopa

Szyjewicz

et al. 2017

Food Bioprocess Technol

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“…3 Time series models are appropriate tools for forecasting monthly rainfall forecasting in semi-arid climates. 4 Determining the most critical rainfall month in each climate condition for agriculture schedules is a recommended aim for future studies.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, ARIMA models are non-static and cannot be used to reconstruct the missing data. However, these models are very useful for forecasting changes in hydrological processes considering agricultural water management, evapotranspiration, and water crisis issues [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Models of time series analysis (Box-Jenkins models) in various fields of hydrology and rainfall forecasting in irrigation schedules are widely applied, some of which will be described in what follows.…”

Section: Introductionmentioning

confidence: 99%

How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations?

Valipour

2016

Agriculture

Self Cite

144

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This paper reports the study of the effect of the length of the recorded data used for monthly rainfall forecasting. Monthly rainfall data for three periods of 5, 10, and 49 years were collected from Kermanshah, Mashhad, Ahvaz, and Babolsar stations and used for calibration time series models. Then, the accuracy of the forecasting models was investigated by the following year's data. The following was concluded: In temperate and semi-arid climates, 60 observation data is sufficient for the following year's rainfall forecasting. The accuracy of the time series models increased with increasing amounts of observation data of arid and humid climates. Time series models are appropriate tools for forecasting monthly rainfall forecasting in semi-arid climates. Determining the most critical rainfall month in each climate condition for agriculture schedules is a recommended aim for future studies.

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“…Also, the re-scaling methods have limitations for areas with high surface type diversity, which particularly refers to wetlands, water containers situated among sub pixel areas. Water surfaces have different emissivity and heat capacity properties and thus they significantly influence the model [29].…”

Section: Pbim Methodsmentioning

confidence: 99%

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

Chybicki¹,

Łubniewski²

2017

Open Geosciences

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Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth's environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR), using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdańsk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255 ∘ C with correlation coefficient R equal to 0.828 and Bias = 0.557 ∘ C. For comparison, using the PBIM method, it was obtained RMSE = 2.832 ∘ C, R = 0.775 and Bias = 0.997 ∘ C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53 ∘ C on average, in the case of applying the proposed method than in the case of using the PBIM method.

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Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events

Cited by 238 publications

References 40 publications

Influence of Contact Surface Type on the Mechanical Damages of Apples Under Impact Loads

Influence of Contact Surface Type on the Mechanical Damages of Apples Under Impact Loads

How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations?

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

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