جستجوی مقالات مرتبط با کلیدواژه « rainfall » در نشریات گروه « اکولوژی »

High-precision precipitation data at the time and place scale, which is a main component of hydrological models, will greatly help to manage the water resources. Hence, in this research, evaluating precipitation data accuracy as well as their origin correction in Quantile method (RQUANT) was used to improve the performance of satellite data in the Yamchi Dam Basin in Ardabil province. The satellite data used included PERSIANN-CCS, PDIR-Now and GPM precipitation data on an hourly, daily and monthly time scale for the region's rainy months over 11 years that were selected by moderate precipitation, standard deviation and coefficient of variation. Comparison of the results obtained from GPM satellite with precipitation data showed that this product has better performance than PERSIANN-CCS and PDIR-Now models on a monthly scale. GPM data on a monthly scale had a MAE index and RMSE 4.66 and 9.70 mm per day, respectively and a correlation coefficient of 0.74; while these values for PERSIANN-CCS and PDIR-Now models were equal to 24.24, 62.03 and 0.36 and 07.09, 13.52, 0.27, respectively. Thus, the GPM satellite precipitation product was provided better performance on a daily scale. Since hourly data was required in flood analysis, then in this paper, precipitation data on an hourly scale was evaluated; the statistical values for GPM satellite were 0.91, 2.66 and 0.06, respectively. In general, among the study precipitation products, GPM precipitation gives better results, although on a daily and hourly scale, the desired results were not obtained compared to the measured data.

In this study, phenology of Salsola laricina as an important range species was studied for period of four years. The phonological stages were recorded at vegetative stage every two weeks and at the reproductive stage once a week. Temperature and precipitation data of the study years were used to interpret the phenology of the species. Results showed that the phenological period of Salsola laricina varied each year due to climate change. Generally, this type of vegetative growth begins in mid-March and continues until mid-July and temporary sleep begins. Flowering occurs in first decade of September and seed ripening stage begin in early November. Generally, the best time to collect seeds is November 10-30, depending on rainfall. Start growing was earlier in the dry year of 2008 (47% lower than long-term) and vegetative period was about 15 to 20 days shorter than in 2009 (16% higher than long-term). Increasing rainfall also increases the vegetative period and delay flowering and seeding about a week. Understanding the phenology of Salsola laricina is important for regulating plant utilization plans, determining the time of entry and exit of livestock, collection of seeds, prevention of untimely harvesting in the steppic rangelands.

Taleghan River is one of the most important rivers in the country because of its flow to Taleghan Dam, which supplies drinking water to this area as well as part of the city of Tehran. Long-term river discharge data are needed to design hydroelectric power stations and manage water resources. Regarding the existing monitoring stations are scattered and cannot provide sufficient hydrological data for the basin we employ rainfall-runoff models which are popular tools for expanding hydrological data over time and space. In this paper, the feasibility of applying a conceptual rainfall-runoff model called HYMOD to a part of Taleghan River Basin is investigated. The generalized probability estimation method was used for model calibration and uncertainty analysis. The results show that the observed discharges are satisfactorily consistent with the observations, indicating that the hydrological model is working well and applying HYMOD to estimate long time series of river discharge in the study area is turning reasonable results.

Annual climate variation, along with water shortage is an important factor influencing agricultural productivity, especially in rainfed crop production systems. Also, understanding the current relationship between food grain production and rainfall will help in assessing the possible impact of future  climate change on the livelihood of smallholder farmers. In Golestan province due to different climates and extended rainfed lands, amount and spatial and temporal distribution of rainfall is very important. In general, the minimum rainfall for dry farming is about 250-300 mm. In addition, distribution of rainfall during the growing period is also noticeable. The enough moisture in vegetation phase is essential for growth and establishment of plant. In this study, spatial analysis of GIS and some methods of classic interpolation and geostatistical methods were used  to evaluate spatial and temporal changes of rainfall variables in the agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships in Golestan province.

This research was carried out in Gorgan University of Agricultural Sciences and Natural Resources (GUASRN), during 2015. The studied region was included the agricultural lands of Aq-Qala, Gonbad Kavous and Kalale townships in Golestan province, as three important regions for  dry farming production. First, the data of 10 synoptic stations and 77 rain-gauge stations from Golestan province were used. The thematic maps of rainfall variables such as annual, autumn, spring, November and May precipitations were provided using various methods of geostatistical and classic interpolation such as Ordinary Kriging (OK), Inverse Distance Weighting (IDW) and Radial Basis Function (RBF) in GIS (var. 10) media. Before interpolation calculations, common statistical tests were performed on main data. The performance criteria for evaluation were Mean Absolute Error (MAE), Mean Bias Error (MBE), Root Mean Square Error (RMSE) and Cross Validation. In this research, a semivariogram function was used to show the variation of rainfalls with respect to distance.

The results showed that Kriging-spherical model was the best method to estimate autumn and May precipitations and also, the annual, spring and November precipitations were interpolated by Multi-quadric (RBF) in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships. Furthermore, the IDW and Thin Plate Spline (TPS) were introduced as inappropriate methods due to high error  in precipitation estimate. The semivariograms analysis indicated that autumn, spring, November and May precipitation variables were the best fitted by Spherical models, but annual precipitation was fitted by Exponential model. It was found that some areas in north of Aq-Qala and Gonbad Kavous had the limitation in amounts of spring and May precipitations. The spatial distribution of precipitations showed that annual precipitation was increased from north to south, so that, the maximum annual precipitation was observed in Kalale township. Thus, this township can be a region with high suitable degree for dry farming some autumn crops such as wheat and barley. The lowest autumn rainfall amount was observed in the northern parts of Gonbad Kavous township with 31.37 mm, but the southern parts of the Aq-Qala, Gonbad Kavous and especially Kalale had the highest autumn precipitation amounts.

Result of the spatial distribution of precipitation showed that amounts of precipitation variables were increased from north to south of the studied region. Totally, among  the three studied townships, Kalale township had the highest amounts of precipitations and the best spatial distribution of precipitation variables for rainfed farming. Therefore, this township was selected as the high suitable region for  dry farming in Golestan province.