Showing 7 results for Forecast
M. Basirat, H. Seyedoleslami,
Volume 5, Issue 1 (4-2001)
Abstract
In winter 1997 severely infested pistachio nuts were collected from orchards in Borkhar district of Isfahan to determine minimum threshold temperature and thermal constants. Minimum threshold temperatures were calculated according to rate of development or X-intercept method and the least coefficient of variation method. Thermal constants were calculated for different developmental stages in the laboratory and were initially compared to field information available.
Results showed that minimum threshold temperatures for covered larvae in nut to 50% pupation, bare larvae to 50% pupation and larvae within nut and 50% pupation to 50% adult emergence according to X-intercept method were 7.69°C, 7.78°C, 9.52°C and 11.14°C, respectively. In the case of least coefficient of variation method, the values were 7.92°C, 7.59°C, 9.81°C and 11.99°C. Thermal constant for occurrence of 50% adult emergence and 50% pupation from overwintering larvae and from 50% pupation to 50% adult emergence and 5% adult emergence to 50% adult emergence with minimum threshold temperatures of 9.5°C, 8°C, 11°C and 11°C under laboratory conditions were 783±17.03, 609±1.7, 215.3±19.05 and 107, respectively, which, except for the last case, they were far different from the thermal constant under field conditions. With regards to the nature of the available data for field conditions, possible reasons have been suggested for these differences.
H. Seyedoleslami, A. R. Hadian, A. Rezai,
Volume 7, Issue 1 (4-2003)
Abstract
High attraction is reported for yellow sticky traps to capture pistachio psylla. In pest management, it is important to forecast from the adult population density the density of other developmental stages in order to gain an estimate of the density in damaging stages. In 1998 and 1999, yellow sticky boards with 10150.15 cm were installed in two pistachio orchards in Borkhar district of Isfahan and egg and nymphal densities were simultaneously counted on leaves. Collected data were used to determine regression relationships between two weeks’ average egg density, first and second nymphal instar densities and the sum of egg and first and second instar nymphal densities, one week after the average adult capture in two previous weeks. A low correlation was found between egg count and adult capture, but higher coefficients were obtained between other stages. It was possible to estimate first and second instar nymphal populations from the following equations:
For high adult densities (X):
Y= 58.6+0.4762X-(7*10-5)X2 R2=0.82 commercial orchard
Y= 27.68+0.5092X-(5*10-5)X2 R2=0.86 abandoned orchard
and for low adult densities (X)
Y= 1.7162X-17.454 R2=0.97 commercial orchard
Y= 1.1117X-4.9841 R2=0.90 abandoned orchard
The application of this method is recommended for the management of pistachio psylla.
S. M. J. Nazemosadat, A. R. Ghasemi,
Volume 8, Issue 4 (1-2005)
Abstract
The influence of the Sea Surface Temperatures (SSTs) on the seasonal precipitation over northern and southwestern parts of Iran was investigated. The warm, cold and base phases of the SSTs were defined and the median of precipitation during each of these phases (Rw, Rc and Rb, respectively) was determined. The magnitude of Rw/Rb, Rc/Rb and Rc/Rw were used as criteria for the assessment of the effects of the alternation of SST phases on seasonal precipitation. The results indicate that in association with cold SST phase, winter rainfall is above median over western and central parts of the coastal region, central and southern parts of Fars Province and all the stations studied in Khozestan Province. On the other hand, the prevalence of warm SST phase has caused about 20% decrease in winter precipitation over the Caspian Sea coastal area and northern parts of both Fars and Khozestan provinces. In association with warm SST phase in winter, precipitation during the following spring was found to be above normal for all the stations studied in the coastal region of the Caspian Sea. The highest sensitivity levels were found in Bandar- Anzali and Astara for which spring precipitation has increased by 80% due to the dominance of warm winter phase. However, the occurrence of boreal cold SST events causes shortage of precipitation in the eastern parts of the coastal areas along the Caspian Sea. A Possible Physical mechanisem justifying the influence of the Caspian Sea SST on the Precipitation variability was introduced. According to this mechanisem, temporal and spatial variability of the Siberian High is forced by the fluctuations in these SSTs.
A. Fatehi Marj, A. Borhani Darian, M. H. Mahdian,
Volume 10, Issue 3 (10-2006)
Abstract
Orumiyeh Lake basin is one of the important regions in Iran from water resources and environment standpoints. In this basin, substantial part of the annual precipitation occurrs in spring, winter, and fall seasons. Due to semi-arid climate of the basin, rainfall forecasting is an important issue for proper water resources planning and management, particularly in drought years. On the other hand, investigations around the world show that there is a good conection between climatic signals and the amount of precipitation. In this paper, the relationship between climatic signals and seasonal rainfall was investigated in Orumiyeh Lake basin. For this purpose, monthly SPI (Standard Precipitation Index) was calculated and used along with six climatic signals including SOI (Southern Oscillation Index), PDO (Pacific Decadal Oscillation), PNA (Pacific North America), NAO (North Atlantic Oscillation), NINO3.4 and, NOI (North Oscillation Index). A new method employing the negative and positive phases of signals was proposed and tested to distinguish the relationship between the climatic signals and the individual stations rainfall in the basin. Furthermore, it was found that using joint signals substantially improves the precision of the forcast rainfalls. The results showed that fall and winter rainfalls had the highest correlatetions with SOI and NAO, respectively. Therefore, it would be possible to forecast the basin rainfall using climatic signals of the previous seasons.
B. Najafi, M. Zibaei, M. H. Sheikhi, M. H. Tarazkar,
Volume 11, Issue 1 (4-2007)
Abstract
In this study wholesale prices of selected crops, namely, tomato, onion and potatoes in Fars province were predicted for various time horizons by using common methods of forecasting and artificial neural networks (ANN). Monthly data from September 1998 to June 2005 period were obtained from Ministry of Jihad-e Agriculture. For comparing different methods data selected from September 1998 to December 2004 were utilized, and latest six - month data were mainly used to monitor the power of prediction. The MAE, MSE and MAPE criteria were used for comparing the ability of different forecasting methods. Results of this study showed that ANN had the lowest error in prediction of prices for one - to three - month periods, but for six - month prediction, all forecasting methods were not statistically different.
N S, A Alizadeh, S Mosa Nejad,
Volume 13, Issue 48 (7-2009)
Abstract
A comprehensive study is underway now to determine the predicting factors of rice blast and its loss assessment in Guilan province. In a preliminary study, the effect of climatic factors on spores population and forecasting the disease were considered. So, during cultivation season of 2006 and 2007, some fields were chosen five kilometers away from weather stations in three regions of Guilan, including, Rasht, Lahijan and Anzali, and the daily spore population was measured on slides. Climatic data including precipitation (mm), maximum and minimum daily temperature, maximum and minimum daily humidity and sunny hours were obtained from weather stations. Then the relation between spore population and weather data was analyzed, and the most important climatic factors affecting spore population and predicting of rice blast were determined. It was concluded that climatic factors such as precipitation (mm), maximum daily temperature, minimum daily humidity and sunny hours are the most important factors for predicting rice blast in Guilan province. Spore population was positively correlated with precipitation, increase of daily minimum humidity, decrease of daily maximum temperature and decrease of sunny hours. The blast disease occurred in the fields during next 7 to10 days.
H. Faghih, J. Behmanesh, K. Khalili,
Volume 22, Issue 1 (6-2018)
Abstract
Precipitation is one of the most important components of water balance in any region and the development of efficient models for estimating its spatiotemporal distribution is of considerable importance. The goal of the present research was to investigate the efficiency of the first order multiple-site auto regressive model in the estimation of spatiotemporal precipitation in Kurdistan, Iran. For this purpose, synoptic stations which had long time data were selected. To determine the model parameters, data covering 21 years r (1992-2012) were employed. These parameters were obtained by computing the lag zero and lag one correlation between the annual precipitation time series of stations. In this method, the region precipitation in a year (t) was estimated based on its precipitation in the previous year (t-1). To evaluate the model, annual precipitation in the studied area was estimated using the developed model for the years 2013 and 2014; then, the obtained data were compared with the observed data. The results showed that the used model had a suitable accuracy in estimating the annual precipitation in the studied area. The percentages of the model in estimating the region's annual precipitation for the years 2013 and 2014 was obtained to be 7.9% and 17.3%, respectively. Also, the correlation coefficient between the estimated and observed data was significant at the significance level of one percent (R=0.978). Furthermore, the model performance was suitable in terms of data generation; so the statistical properties of the generated and historical data were similar and their difference was not significant. Therefore, due to the suitable efficiency of the model in estimating and generating the annual precipitation, its application could be recommended to help the better management of water resources in the studied region.
