Journal of Agricultural Meteorology
Year:2015 | Volume:2 | Issue:2|Papers Count:6

Precipitation which is a key parameter in agricultural and hydrometeorology studies has a large spatio-temporal variation. Hence, its small scale monitoring is quite difficult using ground-based data. Satellite images can provide fine resolution data of rainfall for different applications. However, the temporal and spatial verification should be evaluated and studied before using satellite data. In the present study, daily precipitation data from 12 synoptic and 37 rain gage stations of Fars province, Iran was used to evaluate level 3 B42 version 7 product of the Tropical Rainfall Measuring Mission (TRMM) satellite on a regular spatial scale (0.25o×0.25o) for the period 1998-2011. The Pearson correlation coefficient, mean, median, variance, inter quintiles range (IQR), normalized root mean square error (NRMSE) and mean difference (MD) for daily, monthly, seasonal, yearly time scales were worked out and analyzed. In general, there was a significant correlation between TRMM and ground-based precipitation data over the most parts of the province for all time scale at 5% level such that the range of Pearson correlation for all synoptic (Except for Eghlid) and rain gage (Except for 6 stations) annual time scale was (0.8-0.95) and (0.64-0.93), respectively. The corresponding values for monthly time scale were (0.64-0.96) and (0.5-0.9). The highest and lowest correlation were observed in the monthly and daily time scales respectively. The range of NRMSE for annual, monthly and daily scales were (0.12-0.92), (0.21-0.94) and (0.79-1.91) respectively. In north western parts of the province, which receives more rainfall, positive mean difference values (the mean of observed precipitation was more than that of satellite precipitation) was observed for all time scales. Over eastern parts, in which the amount of precipitation is low, negative MD values were observed. The results of two sample t test indicated that there is no significant difference between means of observed and satellite precipitation for wet months at 5% significance level for 29 stations. Also, the results of F test indicated that the variance of the observed and satellite precipitation for wet months are the same at 5% significance level for 33 stations.

Early blight disease caused by Alternaria solani spreads well in abundance of humidity and the presence of water on the leaves. The early symptoms of disease are brown to black spots as concentric embowed rings. The fungal spores are distributed by wind and rain to healthy leaves. High humidity and temperatures between 18 and 25oC, dew, rain and sprinkler irrigation increase its spread. The purpose of this study was to study the influence of meteorological variables (Temperature, Relative humidity and Precipitation) on spores’ population of early blight pathogen of potato and possible prognosis of disease in Kermanshah province during 2013-2014 crop seasons. To perform the study, potato plants were cultivated in Razi University farm and the symptoms of the disease were monitored continuously through the season. Besides, the number of fungi spores were also measured using a standard spore trap. On the other hand, two early blight prognosis empirical models were developed using on-site meteorological data and those obtained from nearby synoptic station. The correlation between the population of spores in the air and meteorological variables were worked out. The results showed that there exist a significant relation between the spore population and maximum-minimum air temperature (p=0.01) and relative humidity (p=0.05). According to results of this study, the proposed model can be satisfactorily used for early blight early warning in western region of Iran.

Barley (Hordeum Vulgare. L) is an important source of food and second major cereal crop in Iran. The objective of this study is proposing an approach for barley yield forecasting by means of coupling AquaCrop model with several climate teleconnection signals in Kabootarabad-Isfahan, Iran. The experiments were conducted at Kabootarabad agrometeorological station during 2011-2012 and 2012-2013 seasons. The crop model was calibrated using field observations. For validation purpose, the available 15 years historical data were used. Then using 62 years (1951-2013) weather data, crop yield was simulated. Monthly historical records of five phases of SOI (South Oscillation Index) and three phases of IOD (Indian Ocean Dipole) phases for three months prior to planting date (i.e. September, October and November) from 1951 till 2013 were selected and cumulative probability distributions functions of simulated barley yields were worked out for 62 years. Results showed that there are no significant differences between the SOI and IOD phases except for IOD phases of November. Kruskal-Wallis test showed significant differences between IOD phases (P=0.005).Also, Mann-Whitney test indicated that there were significant differences between normal and negative (p=0.012) and positive and negative (p=0.006) IOD phases. Since IOD values are available 3 to 6 months in advance, therefore yield prediction 3 month before sowing might be feasible. During negative and positive IOD phases, using drought resistant cultivars, lower plant densities and other drought mitigation strategies could be considered as management options.

The aim of this study is to investigate the spatial distribution of daily observed precipitation of Iran during baseline (1970-2010) and future (2011-2040) periods using outputs of HADCM3 coupled atmospheric-oceanic (GCM) model. For downscaling these outputs a statistical model namely SimCLIM were used and calibrated. Required data were retrieved from National Center Environmental Prediction (NCEP) which provides a dataset for 1961-2100 period. The data of GCM model of 1970 to 2010 were used. SimCLIM weather generator was applied for, downscaling future prediction during period of 2011-2040. Furthermore, using spatial-statistical tool in Geographical Information System (GIS), the Local Moran and hot spots methods, observed and predicted dispersion and changes of precipitation were examined. The results of the study showed an increasing long-term trend in country's precipitation with average amount of 5.1 millimeter, which is more obvious in Caspian Sea coasts, northwest and also central parts of Iran, especially some parts of Yazd and Isfahan provinces, while precipitation has decreased in southern parts of the country. The results of local Moran spatial analysis of observed and predicted precipitation showed that no-clustered precipitations, that is the low precipitations of southeast and central parts of Iran, have decreased, which indicates the rising trend of precipitation in future period in these regions. Besides, the existence of a cluster of rising precipitation in northeast of the country is observed which indicates that in the future, northeast parts of the country will experience increasing trend of precipitation. This can be confirmed by generated hot spots map also.

Desertification is a major challenge in Iran. In this study, four variables of rainfall, drought duration, aridity index and standard precipitation index (SPI) have been used for monitoring extent of desertification in Kashan plain, Iran. Required data were prepared and scored according to IMPDA scoring table. The obtained criteria were integrated and elaborated in ArcGIS9 software as information layers.Then, each of above mentioned variables were regionalized using proper Krigging method. The maps of each index were generated for three time periods: 1975-1990, 1991-2000 and2001 to 2010. Ultimately, corresponding maps of these three periods were synthesized using geometric average method, and a final climatic map of Kashan plain based on IMDPA model was produced. The results indicated that the severity of desertification increased from south west towards the central and north east parts of the region. The standard precipitation index with the average value of 2.99 had the most significant effect on desertification severity while drought duration with the value of 0.14 had the least influence. Two other indices i, e. drought index and rainfall amount with the values of 2.97, 2.59 ranked in between. In general, it can be concluded that desertification would intensify in future decades.

Calendula officinalis L is a medicinal plant used for manufacturing skin and beauty medication product. Estimating Calendula officinalis water requirement, crop evapotranspiration (ETc) and crop coefficient (Kc) are among the areas which indeed require more research. The study was conducted to calculate Calendula officinalis L. crop coefficients (Kc) and crop evapotranspiration (ETc) because the semi-arid regions face with water scarcity problem; in which management of water resources is vital. This study is performed in Kerman, a city in southeastern Iran with semi-arid climate. In order to estimate the crop evapotranspiration, six lysimeters has been used. The Calendula officinalis were grown in five lysimeters, and the grass reference crop was grown in a lysimeter. Moreover reference evapotranspiration (ETo) has been calculated by Penman-Monteith method, and was compared to ETo obtained from lysimeter. In this study estimated Calendula officinalis crop coefficients in different growth stages were 0.71, 1.28, 1.5 and 0.66, respectively. The Calendula officinalis water requirement for the result obtained from lysimeter was 320.6 mm, also the reference water requirement obtained from lysimeter and Penman-Monteith method was 309.1 mm and 270.1 mm.