Journal of Spatial Analysis

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Changes in the mean and the extreme values of hydroclimatic variables are two
prominent features of the future climate. Therefore, simulating the climatic
behavior of Shandiz catchment area, an important tourist area in the northeast of
the country, will play an important role in identifying the climate condition and
potential vulnerability of these areas in the coming decades of climate change.
In this study, we will
evaluate the effects of climate change on extreme values of the basin micro scaling
precipitation and temperature in CanESM2 model using SDSM model and
simulating runoff with SWAT model in future decades.
To achieve this goal, the daily temperature and precipitation statistics of the 30
statistical years (1961-1990) of Mashhad synoptic station have been
used. The data of the CanESM2 general circulation model under RCP2.6, RCP4.5
and RCP8.5 scenarios are also used to predict precipitation, the minimum and
maximum temperature for 2041 to 2100.
According to the results, the annual precipitation rises 37 to 54 percent from 2041
to2070 compared to the observation period, and the increase in rainfall of the
2071-2100 rises 52 to 66 percent. Precipitation extreme values, the mean of
maximum and minimum temperatures in future periods in all seasons of Mashhad
station will increase compared to the observation period (1961-1990).In future decades, the average maximum temperature in Mashhad will increase from 4.6 to 0.65 degrees Celsius
and the average minimum temperature will increase 53/1 to 22/4.
By introducing micro scaled time series of the maximum temperature, temperature,
and micro scaled precipitation by SDSM model to SWAT model, the monthly time
series of Shandiz watershed runoff at Sarasiab Station was simulated for the two
periods of 2041-2070 and 2071-2100 under three distribution scenarios of RCP2.6,
RCP4.5 and RCP8.5. For this purpose, first, the model was calibrated and validated
using Shandiz hydrometric station runoff for 2003-2012, and the values of R2 were
65 and 52, respectively. Subsequently, with the introduction of micro scaled time
series of maximum and minimum temperatures, and micro scaled precipitation by
SDSM model to SWAT model, the average annual trend shows that runoff
increases in the coming decades. The lowest average annual increase for runoff is
in 2041-2070 and RCP4.5 scenario, with an increase of 56.1% over the observation
period. The highest increase of average annual monthly runoff is from 2071 to2100
under RCP 2.6 scenario with 53% to 104% runoff compared to the observation period.


 

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Evaluation the best of selective base period of GCM models to determine meteorological variables of Birjand station in future periods
 
Abstract:
Nowadays, determining the effect of a climate change in the various aspects of human life is quite evident. In such a situation, it is very important to determine the base period, which determines the effects of a climate change than in this period. Choosing a course-based course plays an important role in choosing future courses to conduct research on the effects of climate change. Many researchers in the research use the LARS-WG dynamic downscale method or the statistical method to measure the weather variables, which should be the same for the years of the base period and the upcoming period.
This research was conducted to select the appropriate base course for estimating minimum temperature, maximum temperature and precipitation at the synoptic station in Birjand. The station is located at latitude 32 degrees and 53 degrees east and 59 degrees and 17 degrees north latitude. In order to evaluate and accuracy of the methods in this research, seven criteria for estimating root mean square error (RMSE) and mean absolute error (MAE), relative error (RD), mean relative error of the month of the year (MRDM), average relative error of the month in the year (RDMM), PBIAS and RSR. In this study, using GCM models, we assessed the selected base courses for the synoptic station in Birjand. To doing in the research, an amount of 27 base courses from 35 models of the fifth report of the change were compared with similar periods obtained from the station in Birjand.
The results showed about precipitation that the duration of the base periods such as 1960-2005 and 1960-2000 is less of the RMSE and MAE errors than the rest of the courses, and the base period of 1965-1990 between periods less than 30 years and the period The 1990-1960s are also well suited to the precipitation data of the synoptic station. The maximum temperature of the 1960-1990, 1960-1985 and 1960-1995 is the lowest RMSE error. However, short-term courses of 1980-1960 and 1965-1985 present satisfactory results.In the case of minimum temperatures, periods of 21 and 31 years 1960-1980, 1960-1985, 1960-1990 and 1965- 1985 have a percentage error of RMSE and a lower percentage of PBIAS. Variable variation range can also be used to show the appropriate base course. The result showed that the periods 1960-2005 and 1970-2005 had a lower range of rainfall variation than the other variables and seems to be more suitable. However, courses such as 1990-2000, 1975-1995, and 1995-2005 have less certainty. The more courses that go into periods with shorter periods of time, the more modest and less certainty they will be. Also, if you look at changes in the 1975-2005 periods and the 1965-1995 periods, it will be clear how much each year towards the years closest to 2005 will be deducted from the precipitation daily average.
The results also show that maximum temperature changes are better than precipitation, and all courses have less variation range. Nevertheless, the period of 1960-2005 has the highest degree of certainty and the period of 1975-2005 has the least degree of certainty compared to the rest of the courses. In contrast to precipitation, there are periods such as 1970-1990, which, if considered as the basis for research, provide more certainty than the longer period of 1965-2005 for maximum temperature. Also, what's most clear about the maximum temperature is the higher the period with years closer to 2005, the temperature increases, which will increase the temperature over time.
The process of minimum temperature variations also indicates that in addition these changes are similar to the change in temperature, with the difference that the range of variations in the minimum temperature is somewhat higher than the maximum temperature. The period of 1960-2005 has the best degree of certainty and the period from 1975-2005 has the least degree of certainty than the rest of the courses. Although long periods of time are less certain than short periods, the result is that the longer the interval between periods increases, the more precise the results will be. The result is not entirely correct, 1975-2000 is less certainty than the 1965-2000 period and has better results in minimum temperatures. Therefore, the evaluation of selected periods of GCM models with similar periods from observations of Birjand station shows that for rainfall variables, periods with a number of years yield more satisfactory results, but for two variables the minimum temperature and maximum temperature of the periods, not long or short periods, provide less risk of RMSE and PBIAS than long periods.
Keywords: climate change, GCM model, base period, meteorological variable, emotion scenario