Ovaj se rad bavi pitanjima identiteta u magijskih praktikanata koji se u hrvatskoj javnosti deklariraju šamanima. Cilj istraživanja bio je uspostavljanje odnosa njihovih tradicija i/ili učenja s ...izvornim šamanističkim sustavom ili sa šamanizmom u širem značenju. Identificirani su i njihovi magijski principi i predodžbe unutar jednoga ili više sustava kojima pripadaju ili ih koriste. Jedan od glavnih problema bio je razmatranje eventualne aporije njihove autoidentifikacije unutar vlastitog odnosa prema izvornome magijskom sustavu i dihotomije kulturne pripadnosti te važnost njihova utjecaja na javnost na općem, zdravstvenom, znanstvenom i kulturnom polju.
ABSTRACT
Evapotranspiration has a significant role in agricultural and forest meteorology research, the hydrological cycle, irrigation scheduling and water resources management. Several models are ...available to estimate evapotranspiration, including mass transfer‐based, radiation‐based, temperature‐based and pan evaporation‐based models. This study aims to assess temperature‐based models versus the Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith model to detect the best one using linear regression under different weather conditions. For this purpose, weather data were gathered from 181 synoptic stations in 31 provinces of Iran. Evapotranspiration was estimated using 11 temperature‐based models and was compared with the FAO Penman–Monteith model. The results showed that the modified Hargreaves–Samani 1 estimates the evapotranspiration better than other models in most provinces of Iran. However, the R2 values were <0.9930 for 20 provinces of Iran. The best precise method was the modified Hargreaves–Samani 4 for Alborz province (AL). Finally, a list of the best performances of each model was presented to use in other regions according to mean, maximum and minimum temperature elevation, minimum and mean relative humidity, sunshine, precipitation and wind speed. The best weather conditions for use in temperature‐based equations (based on the performance of all methods) are 12–18 °C, 18.0–22.5 °C, 5–13 °C, 40–55%, 2.00–3.25 m s−1 and 230–260 h month−1 for mean, maximum and minimum temperatures, relative humidity, wind speed and sunshine respectively. Results are also useful for selecting the best model when researchers must apply temperature‐based models on the basis of available data.
► ETo estimate with limited weather data may cause strong under and overestimations. ► Maps showing under and overestimations of ETo are presented for Mediterranean. ► FAO temperature based method ...for ETo estimate is recommended. ► A correction for aridity and humidity of sites could improve ETo estimate. ► Temperature based ETo methods should be calibrated for local conditions before use.
The standard FAO Penman–Monteith (PM-ETo) method for computing the reference evapotranspiration (ETo), in addition to air temperature, needs data on solar radiation or sunshine duration, relative humidity and wind speed which are often lacking and/or do not respect appropriate quality requirements. Hence, in many cases, ETo has to be estimated with limited weather data using maximum and minimum temperature only. Essentially, two procedures are used when no more than temperature data are available: (i) the well-known Hargreaves–Samani equation (HS), or (ii) the PM-ETo method with weather parameters estimated from the limited available data, called PM temperature (PMT) method. The application of these temperature-based approaches often led to contradictory results for various climates and world regions. The data used in the analysis refer to 577 weather stations available through the CLIMWAT database. The results, confirmed by various statistical indicators, emphasized that: (a) in hyper-arid and arid zones, the performance of HS and PMT methods are similar, with root mean square errors (RMSEs) around 0.60–0.65mmd−1; (b) in semi-arid to humid climates, the PMT method produced better results than HS, with RMSE smaller than 0.52mmd−1; (c) the performance of PMT method could be improved when adopting the corrections for aridity/humidity in the estimation of the dew point temperature from minimum temperature data. The spatial elaboration of results indicated high variability of ETo estimates by different methods. Thus, a site-specific analysis using daily datasets of sufficient quality is needed for the validation and calibration of temperature methods for ETo estimate. Maps presenting indicative results on under/over estimation of ETo by both temperature methods may be useful for their more accurate application over different Mediterranean climates.
The amount of incoming solar energy that crosses the Earth's atmosphere is called solar radiation. The solar radiation is a series of ultraviolet wavelengths including visible and infrared light. The ...solar rays at the Earth's surface is one of the key factor in water resources, environmental and agricultural modelling. Solar radiation is rarely measured by weather stations in Iran and other developing countries; as a result, many empirical approaches have been applied to estimate it by using other climatic parameters. In this study, non-linear models, adaptive neuro-fuzzy inference system (ANFIS) and neural network auto-regressive model with exogenous inputs (NN-ARX) along with empirical models, Angstrom and Hargreaves–Samani, have been used to estimate the solar radiation. The data was collected from two synoptic stations with different climatic conditions (Zahedan and Bojnurd) during the period of 5 and 7 years, respectively. These data contain sunshine hours, maximum temperature, minimum temperature, average relative humidity and solar radiation. The Angstrom and Hargreaves–Samani empirical models, respectively, based on sunshine hours and temperature were calibrated and evaluated in both stations. In order to train, test, and validate ANFIS and NNRX models, 60%, 25%, and 15% of the data were applied, respectively. The results of artificial intelligence models were compared with the empirical models. The findings showed that ANFIS (R2=0.90 and 0.97 for Zahedan and Bojnurd, respectively) and NN-ARX (R2=0.89 and 0.96 for Zahedan and Bojnurd, respectively) performed better than the empirical models in estimating daily solar radiation.
•The ANFIS model with Levenberg–Marquardt algorithm is proposed for modelling solar radiation (SR).•The results are compared with NN-ARX, Angstrom and Hargreaves–Samani models.•Calibrated versions of the empirical models are also considered in estimating SR.•ANFIS models are found to perform better than the NN-ARX and empirical models.
Water use efficiency in agriculture can be improved by implementing advisory systems that support on-farm irrigation scheduling, with reliable forecasts of the actual crop water requirements, where ...crop evapotranspiration (ET
) is the main component. The development of such advisory systems is highly dependent upon the availability of timely updated crop canopy parameters and weather forecasts several days in advance, at low operational costs. This study presents a methodology for forecasting ET
, based on crop parameters retrieved from multispectral images, data from ground weather sensors, and air temperature forecasts. Crop multispectral images are freely provided by recent satellite missions, with high spatial and temporal resolutions. Meteorological services broadcast air temperature forecasts with lead times of several days, at no subscription costs, and with high accuracy. The performance of the proposed methodology was applied at 18 sites of the Campania region in Italy, by exploiting the data of intensive field campaigns in the years 2014-2015. ET
measurements were forecast with a median bias of 0.2 mm, and a median root mean square error (RMSE) of 0.75 mm at the first day of forecast. At the 5
day of accumulated forecast, the median bias and RMSE become 1 mm and 2.75 mm, respectively. The forecast performances were proved to be as accurate and as precise as those provided with a complete set of forecasted weather variables.
Potential evapotranspiration (PET) is a key parameter for climate classification and aridity assessment. The widely used UNEP (1992) classification system is based on the estimation of the aridity ...index AI, which requires annual average values of precipitation P and PET. For the calculation of PET the Thornthwaite's (1948) formula is, in principle, suggested. Recent studies use more advanced and accurate methods for PET estimation but apply to AI the same thresholds proposed by UNEP for aridity classification. This work deals with the uncertainties introduced by the use of different PET methods in the estimation of the aridity index AI. Specifically, the Hargreaves-Samani (HS) method and four of its modifications, three modifications of Thornthwaite's formula and the equation of Hamon, are evaluated against the widely used Thornthwaite's original method, by assessing their impact on the AI. Climatic data as monthly average values of at least 30 years of measurements from 122 stations in the Greek peninsula are used. Results show that AI is highly affected by the PET method adopted, resulting thus to changes in climatic classification of a region. Further, results imply the need for an adjustment of the threshold values that determine aridity classes according to the method each time adopted. Therefore, new threshold values for the aridity classes are developed and presented in this work. The proposed threshold values cover a range of sites that belong to semi-arid SA, sub-humid SH and humid H aridity classes of the Greek peninsula.
•UNEP Aridity Index AI is highly affected by the PET method adopted for its estimation.•10 PET methods effect on AI is assessed for 122 sites over the Greek peninsula.•Uncertainty in aridity classification under Mediterranean climatic conditions.•Most sites were categorized to more arid classes compared to Thornthwaite's approach.•AI adjustment coefficients and threshold values are proposed for each PET method.
This study estimated global potential evapotranspiration (PET) using six climate variables of 14 CMIP6 GCMs at different latitudes of both hemispheres. Hargreaves-Samani (HS) and Penman-Monteith (PM) ...were used to estimate historical and future PETs. To evaluate the historical reproducibility of the six climate variables of the CMIP6 GCMs, five evaluation indicators were used and compared with the NCEP/NCAR reanalysis data. Based on the evaluation metrics, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to calculate the weights for Multi-Model Ensemble (MME) for each band of latitude. After that, the projected annual and seasonal PETs were estimated for the near (2031–2065) and far (2066–2100) futures. The change rate of PET for five timeframes (Annual, Spring, Summer, Fall, and Winter) was calculated for four socioeconomic shared pathways (SSPs). As a result, the PM's PET and HS's PET for all scenarios showed the highest increased signals at 75.5° ∼ 90° in the northern hemisphere (NH) compared to the other latitudes. Especially, the change in the HS of SSP5–8.5 was increased by 26.4% in NH latitude 45.5° to 60° (NL4) compared to the base period. Furthermore, the changes in PET of PM and HS for December, January, and February (DJF) and September, October, and November (SON), and June, July, and August (JJA) lead to remarkably high increases in both hemispheres, irrespective of the level of the emission scenario, completely ignoring the seasonal water cycle in the historical period (1950–2014).
•Since climate variables of CMIP6 GCM differ significantly from each other, MME should be used.•The PET trends of HS have been globally similar to PET of PM in the historical and future periods.•In the far future, the HS and PM trends showed the water cycle in SSP2–4.5 and 3–7.0.•In all scenarios except SSP1–2.6, the high energy for the water cycle was maintained at all latitudes.
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