Shapur Karimi; Babak Aminnejad; Amirpouya Sarraf
Abstract
Global databases provide complete source of required precipitation information for users. The aim of this study is to investigate the accuracy of the TRMM, NCEP and MERRA global precipitation databases in estimating the daily and monthly precipitation in the Balkhaluchai catchment area of Ardabil province. ...
Read More
Global databases provide complete source of required precipitation information for users. The aim of this study is to investigate the accuracy of the TRMM, NCEP and MERRA global precipitation databases in estimating the daily and monthly precipitation in the Balkhaluchai catchment area of Ardabil province. Precipitation data of Nir station the three mentioned databases were extracted from 2002 to 2018. Mann-Kendall, Mann-Whitney and standard normal tests were used to check the trend and homogeneity of precipitation data. For three global precipitation databases, amount of R2, RMSE, NSE, RE and GMER were determined. The results of homogeneity test showed that all P-values were higher than 0.05 and the precipitation data were completely stochastic and homogeneous and no trends were observed in them. In both TRMM and NCEP databases, the R2 coefficient is good and is above 0.6. The MERRA database has had a weaker performance in this case. For the monthly period and the two TRMM and NCEP databases, the NSE index was higher than 0.5, which indicates the reliability of the precipitation data produced in these two stations. At the daily and monthly level, for all three global databases the GMER parameter values were obtained smaller than unity, which indicates that all global databases have overestimates. The overestimation of precipitation for the MERRA global database is much more severe than other two databases. MERRA database has a much weaker performance than NCEP and TRMM databases. In general, the TRMM database has a better efficiency than other databases.
Maryam Rostami; Ali Salajegheh; Forood Sharifi; Arash Malekian; TAYYEBEH MESBAHZADEH
Abstract
AbstractPrecipitation plays an important role in climatic, water, energy and biogeochemical cycles. Several global and regional data sets currently provide historical estimates of this variable over Iran, including the MWEP and WFDEI forcing datasets and production of some institutions such as MOHC, ...
Read More
AbstractPrecipitation plays an important role in climatic, water, energy and biogeochemical cycles. Several global and regional data sets currently provide historical estimates of this variable over Iran, including the MWEP and WFDEI forcing datasets and production of some institutions such as MOHC, SMHI and IITM. All these datasets provide data with different resolutions based on gage stations, satellite Images and models output. In this study, we do an inter comparison between these data sets during 1990- 2008. We also validate all ten data sets against independent ground station observations over 30 second-order basins of Iran. MSWEP and WFDEI have an acceptable compatibility with observational data on different spatial and temporal resolutions. RMSE and Bias are 5.68, 6.34 and 0.58, 2.75 for these two datasets during 228 months, respectively. However, it is needed that MSWEP improves in the western and northwestern parts of the country and WFDEI in June and September months. Our findings in this research provide valuable guidance for a variety of stakeholders, including rainfall- runoff and land-surface modelers, watershed management studies and data providers.
saeed barkhori; elham rafiei sardooi; mohammadreza ramezani; ali azareh; maryam nasabpoor
Abstract
One of the most important and main components of ecosystems is net primary production, which is an important index for assessing the ecosystems performance in the face of environmental changes. To this end, with regards to the importance of the subject, in this study, to quantify the climate change impacts ...
Read More
One of the most important and main components of ecosystems is net primary production, which is an important index for assessing the ecosystems performance in the face of environmental changes. To this end, with regards to the importance of the subject, in this study, to quantify the climate change impacts on ecosystems, NPP values in Jiroft plain was simulated in two periods (2001- 2015and 2016-2030) using the BIOME-BGC model. To assess change in climatic parameters in future, LARS-WG 6 downscaling model was used. After ensuring the capability of the LARS-WG model to create climatic data, climatic variables were simulated in 2016-2030 under the RCP 4.5 scenario. NPP values in 2001-2015 were simulated using the BIOME-BGC model and validated with NPP data derived from Modis images (MOD17A3) that the results showed high accuracy of the model to simulate NPP. After ensuring the model accuracy, NPP was simulated under precipitation and temperature data in future (2016-2030). The results indicate an increase in precipitation, minimum and maximum temperature in the future period (2016-2030) compared with the baseline period (2001-2015). Also, according to the results, NPP value in future has increased in all biomes that this increase is due to increase in precipitation. There is the highest NPP value in the northern and western parts of the region that is related to biome 4 (with agricultural vegetation), biome 5 and 2 (with rangeland vegetation), respectively, and the lowest NPP value is related to the southern parts of the study area.
Khaled Osati; Hamed Joneidi; Nahid Azizi
Abstract
Prediction of rangeland species forage yield is one of the most effective tools for planning and policymaking of natural resources in each country. Climate variables (precipitation and temperature) play an important role in forecasting rangeland species production. In the present study, the forages yields ...
Read More
Prediction of rangeland species forage yield is one of the most effective tools for planning and policymaking of natural resources in each country. Climate variables (precipitation and temperature) play an important role in forecasting rangeland species production. In the present study, the forages yields of some typical species in Ghoosheh rangeland, Semnan, measured using cutting and weighing method. It was evaluated in 30 plots with an area of two square meter, distributed along with two transect lines, for a 10-year period (water year 2005-2006 to 2014-2015), to determine the effects of drought on the forages yield of typical species in the studied areas. In the next step, several drought indices were calculated. The relationship between forages yield of rangeland species and drought indices values investigated to model forages production of study areas via drought indices. According to the values of drought indices SIAP, PNPI and Z-Score, several drought and wet-year periods occurred during the assessed 10-year. The relationship between forages production and drought indices confirmed that the best simple linear regression model for estimating total forages production of studied area was introduced by SIAP and Z-Score indices (RRMSE = 0.1) explaining 53% of production changes at 95% confidence level. The effects of drought and wet-year periods varied among different species so as to the annual production varied greatly for annual species (between 1 and 11% of total annual forages yield) and slightly for perennials and shrubs.
Golnaz Kheradmand; Ali Ariapour; Hamidreza Mehrabi
Abstract
Honey bee husbandry is one of the multipurpose uses of rangelands that it affects by biotic and abiotic factors that investigated in this study for Sarab-Sefid rangeland of Borujerd County. To evaluation of honey bee husbandry suitability used FAO model include four main model plant cover, weather, topography ...
Read More
Honey bee husbandry is one of the multipurpose uses of rangelands that it affects by biotic and abiotic factors that investigated in this study for Sarab-Sefid rangeland of Borujerd County. To evaluation of honey bee husbandry suitability used FAO model include four main model plant cover, weather, topography and distance. Four categories used such as S1 (Suitable), S2 (medium Suitable), S3 (low Suitable) and N (None Suitable). Results show that there is no suitable in April for honey bee husbandry in any part of the area. Also according to mountainous and cold weather in spring and summer subsequently short time to plants growth and according to more grasses families of plants whole area was not in class S1. Honey bee husbandry model in April-May it falls in S3 and N classes with 1152.67 (19.66%) and 4711.76 (80.43%) hec respectively. In May-June months 883.42 (15.06%), 2002.86 (34.15%) and 2978.15 (50.79%) hec falls in S2, S3 and N classes respectively. This result was obtained for June-July so that 799.81 (15.06%), 2437.79 41.57%) and 2626.81 (43.37%) hec falls in S2, S3 and N classes respectively and for July-August-September 799.81 (15.06%) hec in S2 class, 2554.54 (43.56%) hec in S3 and 2509.65 (41.38%) hec fall in N class. Consequently, best time to honey bee husbandry is May to September months.
Abdolhosain Mohammadi; Reza Ghazavi; rohollah Mirzaei; Hamidreza Naseri
Abstract
Rainfall is one of the most important factors affecting vegetation cover. Fluctuation and year-to-year variation of rainfall always affect vegetation cover patterns. The main aim of this study was to investigate and modeling the effects of rainfall changes on the variation of the vegetation cover in ...
Read More
Rainfall is one of the most important factors affecting vegetation cover. Fluctuation and year-to-year variation of rainfall always affect vegetation cover patterns. The main aim of this study was to investigate and modeling the effects of rainfall changes on the variation of the vegetation cover in the Meyghan basin in Arak province using MODIS satellite images. NDVI, DVI, RVI and EVI indices were used to manifest vegetation covert variations linear and nonlinear relationship between vegetation cover changes and rainfall investigated simultaneously (May), with one and two month delay (April and March) ) during the statistical period of 2000-2017. The rainfall trend analysis was done using non-parametric Mann-Kendall test. According to the results, the minimum rainfall during the 18-year period was increased. Between vegetation indices, NDVI index showed the maximum and the average incremental trend. Between precipitation and vegetation, third-order non-linear relationship was stronger than linear, quadratic, power, logarithmic and exponential. The maximum correlation between DVI index and rainfall was obtained for synchronous times, while, the maximum correlation was observed between NDVI index and precipitation. The study with two month delay showed that the maximum correlation (0.52) was between the RVI index and precipitation. Vegetation modeling using simultaneous rainfall and delay of up to two months showed that the indices of DVI, RVI and EVI provided the best regression relationship at the same time, while the NDVI index had the best regression relationship with rainfall of two months ago.
Seyde maryam Alibakhshi; Alireza Faridhosseini; kamran davari; amin alizadeh; Henry Munyka Gathecha
Abstract
Satellite precipitation products have been used in scientific studies in global and regional scales from several decades ago. The purpose of this research is quantitative comparison between TRMM and GPM precipitation products in Kashafrud basin. The important point about these products is their accuracy ...
Read More
Satellite precipitation products have been used in scientific studies in global and regional scales from several decades ago. The purpose of this research is quantitative comparison between TRMM and GPM precipitation products in Kashafrud basin. The important point about these products is their accuracy and pixel size. GPM satellite launched on 28th February 2014 and there is no research in Iran and few in the world. This research aims to assess GPM and its predecessor i.e. TRMM products in comparison with 34 ground rain gauge stations in the basin. Comparisons are done in basin and gauge spatial scales and each in daily and monthly time scales. For validation, the statistical metrics including RMSE, MAE, CC, BIAS, FAR, POD and CSI are used. The results indicated that generally the 3B42V7 product from TRMM has higher accuracy than IMERG product from GPM in our study region. IMERG product only in monthly and basin scale has better accuracy in comparison to 3B42V7 product. Regarding time scale comparison, monthly analysis showed higher accuracy. RMSE value for TMPA product in daily time scale for rain gauge and basin scale is 1.88 and 1.55 and in monthly scales is 2.87 and 2.77, respectively. Also, RMSE for IMERG product in rain gauge and basin in daily time scale is 2.43 and 2.3 and for monthly time scale 3.64 and 2.56, respectively.
Ghader Karimi; Hasan Yeganeh; hasan barati
Abstract
Rangelands have been composed of different plant species that emergence of phenological stages in every one of them will be influenced by environmental and genetic factors. In order to exploit the time and achieve acceptable performance in each plant species, it is necessary that the emergence of biological ...
Read More
Rangelands have been composed of different plant species that emergence of phenological stages in every one of them will be influenced by environmental and genetic factors. In order to exploit the time and achieve acceptable performance in each plant species, it is necessary that the emergence of biological phenomena are recorded and studied. The objective of the present study is to survey the different phenological stages of Bromus tomentellus in order to achieve proper management programs in the study area and similar areas. For this purpose, this study was conducted in semi- steppe rangelands of Kordan located in Alborz province for a 4-year period (2007- 2010). Among the plant species under consideration, ten plant bases were selected and recorded in special forms, during 4 years in the growing season, in 15-day intervals at the vegetative stage and in weekly intervals at reproductive stage, occurrence date of plant critical stages including the stages of the growth and vegetative growth, flowering, seed maturation and drying of the plant, along with the information related to the total height of plant in centimeter. In addition, the meteorological data and information relevant to a four- year study include; average monthly temperature and monthly rainfall from the meteorological station closest to the study area were prepared, and by noting the dry period, the Ombrothermic curves for the years 2007-2010 were separately drawn to adapt to the phenological stages of the study plant. The results indicated that this plant species begins its growth by noting the weather conditions, especially environment temperature (degree-day), in different years of the study period. Different phenological stages also have almost constant temperature demand (GDD), which the emergence of the stages is observed after obtaining the required temperature
Mojtaba Nassaji zavareh; Ali Khorshiddoust; Ali Rasouli; Ali Salajegheh
Abstract
Temperature and precipitation are among important atmospheric parameters for watershed planning. Assessment of temperature and precipitation trends is very important for future watershed planning. In this paper, trends of atmospheric parameters such as seasonal and annual temperature and precipitation ...
Read More
Temperature and precipitation are among important atmospheric parameters for watershed planning. Assessment of temperature and precipitation trends is very important for future watershed planning. In this paper, trends of atmospheric parameters such as seasonal and annual temperature and precipitation were examined for the synoptic stations of Bandar Anzali, Rasht, Ramsar, Babolsar and Gorgan. In order to detect temperature and precipitation trends, homogeneous time series are needed. Expert judgment, metadata and standard normal homogeneity test (SNHT) were used to assess homogeneity of seasonal and annual time series. Some seasonal and annual time series were heterogeneous which were adjusted to homogeneous time series. The results show positive trends of annual and seasonal maximum and minimum temperature, and negative trends of annual and seasonal maximum and minimum precipitation. Also the trend of minimum temperature is higher than the trend of maximum temperature. Mean trends of annual minimum and maximum temperature and annual precipitation are 0.39 ◦c/decade, 0.05◦c/decade and -31/8mm/decade, respectively. The highest average trend of seasonal maximum and minimum temperature is related to the summer season, whereas the highest of average trend of seasonal precipitation is related to the winter season.
The lowest of average seasonal trend of minimum and maximum temperatures are related to the winter and spring seasons, respectively. Mean of seasonal precipitation trends of spring, summer and autumn are almost similar each other.
