Temat: index evapotranspiration - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Wpływ potencjału wody w glebie na ewapotranspirację i plonowanie użytków zielonych
The effect of water potential in soil on grassland evapotranspiration and yielding
Autorzy:: Szajda, J.
Powiązania:: https://bibliotekanauki.pl/articles/337943.pdf
Data publikacji:: 2014
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: ewapotranspiracja rzeczywista
ewapotranspiracja maksymalna użytków zielonych
ewapotranspiracja wskaźnikowa
plon rzeczywisty
plon maksymalny użytków zielonych
potencjał wody w glebach
actual grassland evapotranspiration
maximum grassland evapotranspiration
actual yield from grasslands
maximum yield from grasslands
index evapotranspiration
soil water potential
Opis:: Na podstawie badań polowych na użytkach zielonych określono, dla okresów kwiecień–maj, czerwiec–lipiec i sierpień–wrzesień, współczynniki glebowo-wodne ks1, do oceny wpływu wilgotności gleby na ewapotranspirację rzeczywistą, oraz współczynniki glebowo-wodne ks2, do oceny wpływu wilgotności gleby na plony rzeczywiste, w zależności od bezwzględnej wartości potencjału wody glebowej w warunkach suszy meteorologicznej umiarkowanej, silnej i ekstremalnej, spowodowanej występowaniem ciągów dni bezopadowych definiowanych wg KOŹMIŃSKIEGO [1983, 1986]. Wpływ wilgotności gleby na ewapotranspirację i plon roślin można określić poprzez redukcję wyznaczonych empirycznie maksymalnych wartości ewapotranspiracji [SZAJDA 1997a, b; 2009] i ilości plonów [SZAJDA 1995a,b; 2011] za pomocą tych współczynników. Są one szczególnie przydatne na etapie projektowania melioracji użytków zielonych.
Soil-water coefficients ks1 were determined during field studies in grasslands in April-May, JuneJuly and August-September to assess the effect of soil moisture on actual evapotranspiration. Moreover, coefficients ks2 were determined to assess the effect of soil moisture on actual yields in relation to absolute soil water potential at moderate, severe and extreme drought caused by a set of rain-free periods defined acc. to KOŹMIŃSKI [1983, 1986]. The effect of soil moisture on evapotranspiration and plant yield may be estimated by the reduction of empirically determined values of evapotranspiration [SZAJDA 1997a,b; 2009] and yield [SZAJDA 1995a,b; 2011] using these coefficients. They are particularly useful when designing grassland reclamation.
Źródło:: Woda-Środowisko-Obszary Wiejskie; 2014, 14, 4; 95-122
1642-8145
Pojawia się w:: Woda-Środowisko-Obszary Wiejskie
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Modelling causality between agricultural and meteorological drought indices in the Corong River basin, East Java Indonesia
Autorzy:: Affandy, Nur A.
Iranata, Data
Anwar, Nadjadji
Maulana, Mahendra A.
Prastyo, Dedy D.
Jaelani, Lalu M.
Suryadi, F. X.
Powiązania:: https://bibliotekanauki.pl/articles/28411634.pdf
Data publikacji:: 2023
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: drought
river basin
standard normalisation difference vegetation index
NDVI
standardised precipitation evapotranspiration index
SPEI
time series regression
Opis:: The Lamongan Regency is an area in East Java, Indonesia, which often experiences drought, especially in the south. The Corong River basin is located in the southern part of Lamongan, which supplies the irrigation area of the Gondang Reservoir. Drought monitoring in the Corong River basin is very important to ensure the sustainability of the agricultural regions. This study aims to analyse the causal relationship between meteorological and agricultural drought indices represented by standardised precipitation evapotranspiration index (SPEI) and standard normalisation difference vegetation index (NDVI), using time series regression. The correlation between NDVI and SPEI lag 4 has the largest correlation test results between NDVI and SPEI lag, which is 0.41. This suggests that the previous four months of meteorological drought impacted the current agricultural drought. A time series regression model strengthens the results, which show a causal relationship between NDVI and SPEI lag. According to the NDVI-SPEI-1 lag 4 time series model, NDVI was influenced by NDVI in the previous 12 periods, and SPEI-1 in the last four periods had a determinant coefficient value of 0.4. This shows that the causal model between SPEI-1 and NDVI shows a fairly strong relationship for drought management in agricultural areas (irrigated areas) and is considered a reliable and effective tool in determining the severity and duration of drought in the study area.
Źródło:: Journal of Water and Land Development; 2023, 58; 178--188
1429-7426
2083-4535
Pojawia się w:: Journal of Water and Land Development
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Weather drought index prediction using the support vector regression in the Ansegmir Watershed, Upper Moulouya, Morocco
Autorzy:: Bekri, My Hachem
El Hmaidi, Abdellah
Ousmana, Habiba
El Faleh, El Mati
Berrada, Mohamed
El Aissaoui, Kamal
Essahlaoui, Ali
El Ouali, Abdelhadi
Powiązania:: https://bibliotekanauki.pl/articles/1841959.pdf
Data publikacji:: 2021
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: Ansgemir watershed
drought
forecast
modelling
standardized precipitation index
SPI
standardized precipitation-evapotranspiration index
SPEI
support vectors regression
SVR
Opis:: The purpose of this study is to develop mathematical models based on artificial intelligence: Models based on the support vectors regression (SVR) for drought forecast in the Ansegmir watershed (Upper Moulouya, Morocco). This study focuses on the prediction of the temporal aspect of the two drought indices (standardized precipitation index – SPI and standardized precipitation-evapotranspiration index – SPEI) using six hydro-climatic variables relating to the period 1979–2013. The model SVR3-SPI: RBF, ε = 0.004, C = 20 and γ = 1.7 for the index SPI, and the model SVR3-SPEI: RBF ε = 0.004, C = 40 and γ = 0.167 for the SPEI index are significantly better in comparison to other models SVR1, SVR2 and SVR4. The SVR model for the SPI index gave a correlation coefficient of R = 0.92, MSE = 0.17 and MAE = 0.329 for the learning phase and R = 0.90, MSE = 0.18 and MAE = 0.313 for the testing phase. As for the SPEI index, the overlay is slightly poorer only in the case of the SPI index between the observed values and the predicted ones by the SVR model. It shows a very small gap between the observed and predicted values. The correlation coefficients R = 0.88 for the learning, R = 0.86 for testing remain higher and corresponding to a quadratic error average MSE = 0.21 and MAE = 0.351 for the learning and MSE = 0.21 and MAE = 0.350 for the testing phase. The prediction of drought by SVR model remain useful and would be extremely important for drought risk management.
Źródło:: Journal of Water and Land Development; 2021, 50; 187-194
1429-7426
2083-4535
Pojawia się w:: Journal of Water and Land Development
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Climatic and anthropogenic drivers of zero-flow events in intermittent rivers in Poland
Autorzy:: Rutkowska, Agnieszka
Osuch, Marzena
Żelazny, Mirosław
Banasik, Kazimierz
Klimek, Mariusz
Powiązania:: https://bibliotekanauki.pl/articles/27312644.pdf
Data publikacji:: 2023
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: circular statistics
climatic impact
anthropogenic impact
river flow intermittence
standardised evapotranspiration index
trend in flow intermittence
Opis:: River intermittence was studied based on data from hydrological monitoring in Poland. We screened the entire state database and two another data sources applying the criterion for zero-flow event: discharge less than 0.0005 m3∙s-1, and found five intermittent rivers with catchment area from 9.2 to 303.7 km2. We aimed at finding associations between intermittence and climatic driving forces (temperature and precipitation), and between intermittence and anthropogenic activity. We used the Spearman correlation coefficient, circular statistics, and statistical tests for trend. The concentration of zero-flow days, mostly in summer, and the decreasing trend in the standardised precipitation evapotranspiration index (SPEI) in all catchments at various aggregation levels, and an increasing trend in the total number of zero-flow days and in the maximum length of zero flow events in two rivers, were detected. The strong negative correlation (–0.62 ≤ ρ < 0) between intermittence and the SPEI backward lagged in time showed that intermittence resulted from prolonged deficits in climatic water balance due to increasing evapotranspiration. The reaction of the Noteć catchment, amplified by the anthropogenic pressure (brown coal mines), was reflected in the atypical shape of the rose diagram and in inhomogeneities in river discharges. The results show that the rose diagram can serve as an indicator of the degree of anthropogenic impact on runoff conditions.
Źródło:: Journal of Water and Land Development; 2023, 57; 52--61
1429-7426
2083-4535
Pojawia się w:: Journal of Water and Land Development
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Integration Remote Sensing and Meteorological Data to Monitoring Plant Phenology and Estimation Crop Coefficient and Evapotranspiration
Autorzy:: Hassan, Diaa Fliah
Abdalkadhum, Aysar Jameel
Mohammed, Rafal J.
Shaban, Amin
Powiązania:: https://bibliotekanauki.pl/articles/2086414.pdf
Data publikacji:: 2022
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: actual evapotranspiration
crop coefficient
remote sensing
vegetation index
Opis:: The water requirements of the wheat crop are represented by the actual evapotranspiration, which depends on the meteorological data of the study area and the amount of water consumed during the season. Estimation of crop coefficients (Kc) and evapotranspiration (ETc) using remote sensing data is essential for decision-making regarding water management in irrigated areas in arid and semi-arid large-scale areas. This research aims to estimate the crop coefficient calculated from remote sensing data and the actual evapotranspiration values for the crop. The FAO Penman-Monteith equation has been used to estimate the reference evapotranspiration from meteorological data. Linear regression analysis was applied by developing prediction equations for the crop coefficient for different growth stages of comparing with the vegetation cover index (NDVI). The results showed that (R2 = 0.98) between field crop coefficient and crop coefficient predicted from (Kc = 2.0114 NDVI-0.147) in addition to (RMSE = 0.92 and (d = 0.97).
Źródło:: Journal of Ecological Engineering; 2022, 23, 4; 325--335
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Irrigation Needs in Ukraine According to Current Aridity Level
Autorzy:: Lykhovyd, Pavlo
Powiązania:: https://bibliotekanauki.pl/articles/1955473.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: aridity index
evapotranspiration
humidification
precipitation
soil moisture regime
Opis:: Global climate change has led to significant shifts in local climatic conditions of Ukraine with the trend to aridity aggravation. Sustainable crop production is at risk due to the aridity level increase. The study is aimed to evaluate aridity index in Ukraine (on the whole country and individual regions’ scales) and the needs in irrigation using hydro-meteorological data of the key regional stations for the periods of 1961-1990 and 2010-2020. The results of hydro-meteorological evaluation were supported by the data on the soil moisture regimes provided by Soil Explorer service. The general trend to aridity aggravation in Ukraine was proved. It was found out that modern climate in most territory of Ukraine is semi-arid, dry subhumid and humid zones are observed in the western regions only. Humid soil moisture regimes (ustic and udic) are observed in the West and the North of the country. As a result of combined analysis of both aridity index and soil moisture regimes the conclusion was drawn that 46.05% of Ukrainian croplands cannot provide sustainable crop production without irrigation, 42.65% need irrigation for the cultivation of crops with high water use, and just 11.30% of the arable land require little or no irrigation.
Źródło:: Journal of Ecological Engineering; 2021, 22, 8; 11-18
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki