جستجوی مقالات مرتبط با کلیدواژه « بارش موثر » در نشریات گروه « جغرافیا »

Among the various environmental stresses and hazards, drought is recognized as the most important environmental factor, which is the main challenge in different parts of the world, especially in the Middle East, in addition to widespread effects on agricultural production and productivity, effects on the other social and economic dimensions of humans. Therefore, drought analysis, monitoring, and characterization are one of the main necessities of drought management and planning. In this study, the trend of agricultural drought in the Gonabad region was identified and evaluated by the Reconnaissance Drought Index (RDI) and its improved version, the effective Reconnaissance Drought Index (eRDI) for 59 years (1982-1920). The results showed that there was no significant difference between the indices, although the eRDI index was more sensitive and accurate in seasonal periods. The longest drought period was obtained for 9 years through the eRDI FAO index and the longest wet period was calculated for 11 years by all indices. Also, the highest frequency of weather conditions was related to the normal situation (33.9 to 39%). On a seasonal scale, the longest droughts and wet periods were calculated in spring for 8 and 6 years, respectively. These conditions were 7 and 6 years for autumn and 9 and 7 years for winter, respectively. All indicators identified wet conditions for the summer. In general, although the eRDI index can be more efficient in determining and monitoring the agricultural drought due to the use of effective precipitation instead of cumulative rainfall, in this study no significant difference was observed between the two indicators. Therefore, seems that the RDI index can be used in drought monitoring and analysis in climatic regions similar to the study area.

One of the most important issues related to rainfed wheat cultivation is the date of the First Effective Precipitation (FEP) which can provide soil moisture for cultivation. The current study aims to evaluate the variability and probable trend in the date of the first effective precipitation and the synoptic conditions that lead to its occurrence in northwestern and western Iran. Therefore, precipitation data were extracted from Iran’s Meteorological Organization. First precipitation with a value of at least 5 mm and duration of one to two consecutive days, associated with another precipitation occurring less than 10 days apart, was selected as the first effective precipitation. Then, the trend of first effective precipitation was investigated using Man-Kendall test and linear regression method. Finally, geopotential height, wind speed and humidity data (ERA-Interim) at 850 and 500 hPa levels were obtained from ECMWF website to identify synoptic patterns of the first effective precipitation by cluster analysis method. The findings reveal that more than 90% of the first effective precipitation has occurred during October. Accordingly, Ardebil, Sanandaj, Khorramabad, Kermanshah, Zanjan, Orumieh, Tabriz and Hamadan stations had earliest climatic average of the first effective precipitation date during the period of 1987 to 2016, respectively. Despite the high annual variations regarding the occurrence date of first effective precipitation, evaluating the trend of the first effective precipitation by Mann-Kendall test at the significant level of 5% show that there is no significant trend in all studied stations. Furthermore, synoptic patterns including the short trough, omega block, cutoff low and the Mediterranean long trough are identified as responsible patterns on the occurrence date of the first effective precipitation. Among the patterns, omega block has been associated with widespread rainfall at the studied stations due to greater access to moisture and unstable conditions caused by the cold weather.

Among factors affecting crop production, especially rainfed crops, the rainfall and its distribution during crop season have a significant role. In addition, all the precipitation that falls during the growing season does not have the same effect on crop yield, and is not used in agriculture. So, quantification of Effective Rainfall (ER), as a portion of the precipitation which is stored in plant root zone and meets the needs of evapotranspiration requirements in different climatic zones is an essential component of water resources in rainfed wheat areas. Effective rainfall used in this study is “That portion of the total precipitation on the cropped area, during a specific time period, which is available to meet the potential evapotranspiration requirements in the cropped area. A precise estimation of effective rainfall is still needed not only for planning and management of rainfed wheat production, but also for risk management strategies in farms. Since a precise estimation of effective rainfall is necessary for increasing agricultural production, major challenge is to design a soil-water balance model that provides more accurate calculation of effective rainfall. The main goal of this study was to compare different effective rainfall estimation methods for rainfed wheat. In this study, we adopted a two-layer soil–water balance (SWB) model. In the model,not only the portion of precipitation retained on root zone in current day is included, but a portion of the previous day’s precipitation saved between the previous and current root-zone development is also added to the effective rainfall of the current day. In the model, the soil reservoir is divided into two layers; 1) an active layer in which roots are presented at any given time, t, and from which both moisture extraction and drainage could occur; 2) immediately below the active layer, there is a passive layer of depth (maximum root depthroot depth attained any day after sowing) from which only drainage would occur. Because of a high cost associated with direct measurements, estimate of effective rainfall component is often based on empirical models. The aim of this study is to compare empirical methods of effective rainfall estimation with a proposed method based on soil-water balance equation. Following, six methods have been used to calculate effective rainfall for 21 agrometeorological stations of Iran:• Renfro Equation method • U.S. Bureau of Reclamation method • Potential Evapotranspiration/Precipitation Ratio method • USDA-SCS method • FAO method • TR21/SCS method For this purpose, four groups of data (including weather data, phenological data, soil characteristics, and wheat yield data) were used relevant to the 21 agro-meteorological stations representing arid, semi-arid, semi-humid, and humid regions of the country. Before using the weather data for estimating effective rainfall, data reconstruction was performed using Normalratio method (where required). The results of calculating the effective rainfall for rainfed wheat crop at the 21 agrometeorological stations, using selected methods and comparing the different methods of estimating effective rainfall, showed that: 1) in spite of data limitations, the new procedure had appropriate performance in estimation of that part of wheat yield which could only be explained by effective rainfall. Therefore, this method can be used as an efficient tool in computer based programs developed for agricultural risk management of rainfed area. 2) It has been observed that the higher the values of de Martonne Aridity Index, the lower is value of “effective rainfall/rainfall during the cropping season”. 3) The best result for arid and semi-arid climates was obtained by PET/P method (d-index= 0.8), and for semi-humid and humid climates by FAO method (respectively 0.9 and 0.8), and USDA-SCS method (respectively 0.8 and 0.7). A soil water balance model for estimating effective rainfall is applied for evaluating the accuracy of six established effective rainfall estimation methods. Renfro Equation provides an initial approximation based on aridity factor. The accuracy of this method is very low and it is exclusively empirical. USBR method considers only the runoff. The accuracy of this method is low and is not suitable for wide application. PET/Precipitation Ratio method takes the first approximation by runoff, soil and aridity factor. This method is suitable for preliminary plans, and is more effective than other methods, nearly in all regions. USDA- SCS method takes the first approximation of soil and crop beside aridity factor. This method is suitable for those areas that have low intensity of rainfall and high infiltration rate.