Wyniki wyszukiwania - Biblioteka Nauki

1

Use of conventional and satellite data for estimation of evapotranspiration spatial and temporal pattern

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Struzik P. , Kępińska-Kasprzak M.

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tom Vol. 4, iss. 2

3--13

EN

Evapotranspiration values (ET) are crucial for agriculture where estimates of water reserves available for crops are the basis for scheduling the time and intensity of irrigation, yield prognoses, etc. Detailed evapotranspiration data are, therefore, of essential value. However, stations performing direct measurements of evapotranspiration are very scarcely distributed in Poland, and for this reason the interpolation of data is necessarily biased. Hence, evapotranspiration values are calculated using indirect methods (usually empirical formulas). Data from geostationary meteorological satellites are used operationally for the determination of evapotranspiration with good spatial and temporal resolution (e.g. Land-SA F product). The study of the relation between evapotranspiration values determined with the use of satellite data and those calculated using the Penman-Monteith formula was performed for the study area in Poland. Daily values and cumulated (i.e. decadal, monthly and yearly) values were analysed to determine the quality and possible added value of the satellite product. The relation between the reference ET and actual ET in two consecutive years was discussed, both for the whole test area and for individual stations, taking into account land use and possible water deficit in the root zone, represented by H-SA F (EUMETSA T Satellite Application facility supporting Operational Hydrology and Water Management) soil wetness index product. The differences are presented and discussed.

2

Estimating Reference Evapotranspiration Using Penman-Monteith (FAO-56-PM) Method from Limited Data in Fan and Pad Greenhouses

86%

Gaafer A. M. A. , Mohammed H. I. , Elfadil A. D.

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tom 53

49-59

EN

ABSTRACT Determination of reference evapotranspiration (ETo) in required for design, management and scheduling of irrigation water in fan and pad greenhouses. In actual practice estimation of (ETo) in fan and pad greenhouses is often made using the Penman-Monteith FAO-56-PM; method from external meteorological data. This requires availability of accurate meteorological input data (temperature, relative humidity, wind speed, and solar radiation). This is constrained by lack of such data which is a common problem in developing countries. In this study the proposed procedure to estimate ETo is based on using limited data of outdoor historically recorded climate elements of only temperature wind speed, and site characteristics (altitude, latitude and sun shine hours). In the proposed method radiation is to be predicted from data of air temperature difference rather than its direct measurement. This because radiation measurement using pyranometers and net radiometers is borne to errors calibration errors commonly plagued by hysteresis, and nonlinearity. The obtained results of the proposed alternative procedure were statistically validated in comparison with the standard method (FAO 56 PM) using unlimited input data measured inside the greenhouse and in reference to a directly measured ETo values by class-A-evaporation pan. The performance of the developed model was evaluated by the determination coefficient of the regression "R2 for goodness-of-fit" and by using the Root Mean Square Error (RMSE). The needed data is collected during three years in three sites in Khartoum North-Sudan El Alafoon, Halfaya, and Shambat. In each site three greenhouses were employed, and data is taken every three days for three months in each year. The obtained result reveals that the proposed limited data procedure to estimate the ETo inside greenhouses agree on statistical basis well with both pan measurement and PM estimation from measured indoor climate variables. The study reveals importance of temperature data for estimating ETo in greenhouses and calls for insuring high quality temperature data for calculating ETo in fan and pad greenhouses.

3

Porównanie ewapotranspiracji wskaźnikowej obliczanej na podstawie pomiarów wykonanych na standardowej i automatycznej stacji agrometeorologicznej

86%

Łabędzki L. , Kasperska-Wołowicz W.

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tom T. 2, z. 2

21--31

PL

Powszechnie stosowaną metodą obliczania ewapotranspiracji upraw rolniczych jest metoda współczynników roślinnych, polegająca na mnożeniu ewapotranspiracji wskaźnikowej przez empiryczny współczynnik roślinny. Współczynniki roślinne zostały określone w wieloletnich pomiarach lizymetrycznych ewapotranspiracji i odniesione do ewapotranspiracji wskaźnikowej obliczanej według wzoru Penmana na podstawie pomiarów meteorologicznych na stacji standardowej. Wprowadzenie nowej, automatycznej metody zbierania i przetwarzania danych meteorologicznych zrodziło pytanie, czy ewapotranspiracja wskaźnikowa liczona na podstawie pomiarów automatycznych różni się od liczonej na podstawie pomiarów standardowych. Pomiary na standardowej i automatycznej stacji agrometeorologicznej prowadzono jednocześnie od 11 czerwca do 30 września 1997 roku w dolinie Noteci. Sumy dekadowe ewapotranspiracji wskaźnikowej obliczanej na podstawie pomiarów na stacji automatycznej były o 1–8 mm mniejsze od obliczanych metodą standardową. Stosowanie ewapotranspiracji wskaźnikowej obliczanej na podstawie automatycznych pomiarów z dotychczasowymi wartościami współczynników roślinnych może prowadzić do zaniżania obliczonych wartości ewapotranspiracji rzeczywistej roślin. W związku z tym należałoby określić i stosować współczynniki do przeliczania wartości współczynników roślinnych lub ewapotranspiracji wskaźnikowej, jednak biorąc pod uwagę dokładność obliczania ewapotranspiracji rzeczywistej roślin potrzebną do określania ilości wody do nawodnień, stwierdzone różnice ewapotranspiracji wskaźnikowej nie są znaczące.

EN

The crop factor method is commonly used to estimate evapotranspiration under conditions of sufficient water supply. It is an indirect method based on estimation of reference evapotranspiration and crop coefficients. The crop coefficients are determined from multiannual local lysimeter experiments as the ratio of measured evapotranspiration to calculated reference evapotranspiration. Up-to-day the reference evapotranspiration was estimated with the use of standard meteorological measurements. Introducing new (automatic) method of collecting and processing meteorological data causes the problem whether the reference evapotranspiration calculated from automatic measurements differs from that calculated from standard measurements. If so, then the crop coefficients should be adjusted to the new method of reference evapotranspiration estimation. Studies were carried out in the period between 11 June and 30 September 1997 in the upper Noteć river valley. Ten-day period sums of reference evapotranspiration estimated from automatic station were 1-8 mm lower than those calculated with the standard method. Using mean 24-hour meteorological data obtained with the automatic station and the crop coefficients determined with the standard method of meteorological measurements underestimated actual evapotranspiration of crops. Therefore, factors for the crop coefficient or for the reference evapotranspiration should be corrected. However, taking into account the accuracy of calculation of actual evapotranspiration for the estimation of irrigation water requirements, the differences in reference evapotranspiration are not significant.

4

Modeling daily reference evapotranspiration using SVR machine learning algorithm with limited meteorological data in Dar-el-Beidha, Algeria

58%

Salah Z. , Khaled B.

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tom Vol. 72, no. 3

2009--2025

EN

Reference evapotranspiration (ETo) is a critical water resource management parameter, including irrigation scheduling and crop water requirements. Because large uncertainties in estimating ETo can result in equally large uncertainties in determining water budgets and crop water requirements, and vice versa, accurate determination of ETo can be challenging when direct measurement and estimation with the Penman-Monteith (FAO-56-PM) semi-empirical equation of the food and agriculture organization (FAO) is not possible. Indeed, this study explores the use of the support vector regression machine learning algorithm (SVR) to predict daily ETo with limited measured inputs. It is the first time that Julian Day (J) is included as an input to improve prediction accuracy. Ten years of meteorological data collected at the Dar-El-Beidha weather station in Algeria are used, with maximum, minimum, and mean air temperatures (TM, tm, and T), mean relative humidity (RH), mean wind speed (u2), and sunshine duration (n) as inputs, as well as J and extraterrestrial solar radiation (Ra) as auxiliary variables, and the ETo-FAO-56-PM values as target outputs. Several SVR models are developed using different combinations of inputs, and their performance is assessed relative to ETo-FAO-56-PM values. Empirical equations are also used for comparison, and several evaluation metrics are employed, including root mean square error (RMSE), mean absolute percentage error (MAPE), determination coefficient (R2), RMSE-standard deviation ratio (RSR), Nash-Sutcliffe efficiency coefficient (NSE), and Willmott’s refined index (WI). The results show that the SVR models utilizing limited meteorological inputs in addition to J and/or Ra predicted ETo accurately and outperformed their corresponding estimates using empirical equations, radial basis function neural networks (RBFNN), and adaptive neuro-fuzzy inference systems (ANFIS) models obtained in previous studies. The RMSE ranged from 0.28 to 0.72 mm/day, R2 from 0.86 to 0.98, MAPE from 7 to 19%, RSR from 0.15 to 0.38, NSE from 0.86 to 0.98, and WI from 0.65 to 0.87. These findings could provide useful solutions for ETo estimation issues in areas with sparse data and agro-climatic conditions similar to those of Dar-El-Beidha.