ارزيابي اثراقليم بر خشكسالي كشاورزي به كمك شاخص هاي SPI و ETDI

The evaluation of effect of climate change on agricultural drought using ETDI and SPI indexes

ﺳﺎﺑﻘﻪ و ﻫﺪف: ﺑﻪ دﻟﯿﻞ واﺑﺴﺘﮕﯽ ﮐﺸﺎورزي ﺑﻪ آب، ﺗﻌﯿﯿﻦ ﺷﺮاﯾﻂ ﺧﺸﮑﺴﺎﻟﯽ در ﻫﺮ ﻣﻨﻄﻘﻪ ﺑﻪ ﻣﻨﻈﻮر ﺑﺮﻧﺎﻣﻪ رﯾﺰي ﺗﺄﻣﯿﻦ ﻏﺬا ﻣﻬﻢ اﺳﺖ .ﻣﺘﺄﺳﻔﺎﻧﻪ ﭼﻮن ﺗﻌﺮﯾﻒ ﯾﮑﺴﺎﻧﯽ از ﺷﺮاﯾﻂ ﺧﺸﮑﺴﺎﻟﯽ وﺟﻮد ﻧﺪارد؛ ﺷﺎﺧﺺ ﻫﺎي ﻣﺘﻌﺪدي براي آن ارائه شده است . شاخص بارش استاندارد شده ( SPI ) يكي از شاخص هاي مهم هواشناسي است كه به منظور تعيين خشكسالي هاي كشاورزي مورد استفاده قرار مي گيريد. .ﺷﺎﺧﺺ ﮐﻤﺒﻮد ﺗﺒﺨﯿﺮ- ﺗﻌﺮق ( ETDI ) نيز يكي از شاخص هاي مﻬﻢ اﺳﺖ ﮐﻪ ﺑﻪ ﻣﻨﻈﻮر اﺳﺘﻔﺎده در ﺑﺨﺶ ﮐﺸﺎورزي اراﺋﻪ ﺷﺪه اﺳﺖ .اﯾﻦ ﺷﺎﺧﺺ در ﻣﻨﺎﻃﻖ ﺧﺸﮏ و ﻧﯿﻤﻪ ﺧﺸﮏ ﮐﺎرﺑﺮد دارد.ﺑﺎ وﺟﻮد اﯾﻦ ﮐﻪ ﭘﮋوﻫﺶ ﻫﺎي ﻣﺘﻌﺪدي در ﺧﺼﻮص ﺷﺎﺧﺺ وﺟﻮد دارد، ﺗﺎﮐﻨﻮن SPI ﻫﺎي ﺧﺸﮑﺴﺎﻟﯽ از ﺟﻤﻠﻪ اﻧﺠﺎم ﺷﺪه اﺳﺖ .ﺑﻨﺎﺑﺮاﯾﻦ در اﯾﻦ ﭘﮋوﻫﺶ ETDI ﻣﻄﺎﻟﻌﺎت اﻧﺪﮐﯽ ﻓﻘﻂ در ﺧﺎرج ﮐﺸﻮر در ﺧﺼﻮص ﮐﺎرﺑﺮد ﺷﺎﺧﺺ ﺗﻌﯿﯿﻦ ﺧﺸﮑﺴﺎﻟﯽ ﺑﺎ اﺳﺘﻔﺎده از ﺷﺎﺧﺺ،ﺳﻌﯽ ﺷﺪ در دﺷﺖ ﻧﯿﺸﺎﺑﻮر ﺑﻪ ﮐﻤﮏ ﻣﺪلﻫﺎي ﺗﻐﯿﯿﺮ اﻗﻠﯿﻢ SPI و ETDI ﻫﺎي اﻧﺠﺎم ﺷﻮد . ﻣﻮاد روش ﻫﺎ: اﯾﻦ ﭘﮋوﻫﺶ ﺑﻪ ﻣﻨﻈﻮر ﺗﻌﯿﯿﻦ ﺧﺸﮑﺴﺎﻟﯽ در دﺷﺖ ﻧﯿﺸﺎﺑﻮر واﻗﻊ در ﻋﺮض ﺟﻐﺮاﻓﯿﺎﯾﯽ و ﻃﻮل ﺟﻐﺮاﻓﯿﺎﯾﯽ انجام شد. شاخص ETDI براساس كمبود تبخير- تعرق هفتگي در اين منطقه تعيين شد. به منظور مقايسه نتايج شاخص ETDI نسبت به ساير شاخص هاي خشكسالي ، از شاخص SPI كه يكي ار مهم ترين شاخص هاي مورد استفاده در اين خصوص است ، استفاده شد. داده هاي مورد نياز اين پژوهش ار ايستگاه هواشناسي نيشابور در بازه 1373 تا 1390( 1992تا 2011) گرفته و براي مزارع آبي ( مزارع گندم فاروب و سليماني ، جو و ذرت ) و مزارع ديم ( براي گندم ديم ) استفاده شد .براي تعيين هواشناسي مورد نياز هر شاخص درمزارع آبي در دوره هاي آتي ( 2020 تا 2039 و 2080تا 2099)از مدل هاي HADCM3و ECHAM ، و CGCM3 T47 براساس سناريو هاي A2، B1 ، A1B استفاده شد. براي مزارع ديم نيز ار مدل HADCM3 بر اساس سناريوهاي A2 و B1 استفاده گرديد. آمارهاي ميانگين مربعات خطا ( RMSE )،ميانگين خطاي مطلق (MAE) ، ضريب تعيين ( R2 ) نيزبراي مقايسه نتايج دو شاخص ETDI و SPI مورد استفاده قرار گرفتند. ﯾﺎﻓﺘﻪ ﻫﺎ: ﻧﺘﺎﯾﺞ ﻧﺸﺎن داد ﮐﻪ ﺷﺎﺧﺺETDI ﺑﺮاي ﻣﺰرﻋﻪ ﻓﺎروب در دوره ﭘﺎﯾﻪ (1992تا 2011) در ﺣﺎﻟﺖ "رﻃﻮﺑﺖ اوﻟﯿﻪ ﻗﺮار داﺷﺖ در ﺣﺎﻟﯽ ﮐﻪ در دوره هاي آتي ( 2020تا 2039 و 2080 تا 2099) در ﺣﺎﻟﺖ "ﺧﺸﮑﯽ" ﺗﻌﯿﯿﻦ ﺷﺪﺷﺎﺧص IETD ﺑﺮاي ﻣﺰرﻋﻪ ﺳﻠﯿﻤﺎﻧﯽ در دوره ﭘﺎﯾﻪ در ﺣﺎﻟﺖ "ﻧﺮﻣﺎل" ﻗﺮار داﺷﺖ .اﯾﻦ ﺷﺎﺧﺺ ﺑﺮاي ﻣﺰرﻋﻪ ﺳﻠﯿﻤﺎﻧﯽ در دوره هاي 2020تا 2039 و 2080تا 2099 بهﺗﺮﺗﯿﺐ در ﺣﺎﻟﺖ ﻫﺎي "ﻧﺮﻣﺎل" و "ﺧﺸﮑﯽ اوﻟﯿﻪ" ﺗﻌﯿﯿﻦ ﺷﺪ .ﺷﺎﺧﺺ ETDI در دوره ﭘﺎﯾﻪ ﺑﺮاي ﻣﺰارع ﺟﻮ و ذرت ﺑﻪﺗﺮﺗﯿﺐ در ﺣﺎﻟﺖ ﻫﺎي "ﻧﺮﻣﺎل" و "ﺧﺸﮑﯽ اوﻟﯿﻪ" ﻗﺮار داﺷﺖ .اﯾﻦ ﺷﺎﺧﺺ ﺑﺮاي ﻫﺮ دو ﻣﺰرﻋﻪدو دوره هاي آتي در ﺣﺎﻟﺖ "ﻧﺮﻣﺎل" ﻗﺮار ﮔﺮﻓﺖ.ﻣﻘﺪار ﺷﺎﺧﺺ ETDI براي گندم ديم در دوره ﭘﺎﯾﻪ ﮐﻢ ﺗﺮ از ﮔﻨﺪم آﺑﯽ ﺑﻮد در ﺣﺎﻟﯽ ﮐﻪ ﻋﮑﺲ اﯾﻦ ﺣﺎﻟﺖ در دوره آﺗﯽ ﻣﺸﺎﻫﺪه ﺷﺪ . ﺑﺎ اﺳﺘﻔﺎده از اﮐﺜﺮ ﺳﻨﺎرﯾﻮﻫﺎي تغيير اقليم ، شاخص ETDI ﻣﻘﺪاري ﻣﻨﻔﯽ داﺷﺖ .اﯾﻦ ﻧﺸﺎن دﻫﻨﺪه ﺑﺮوز ﺧﺸﮑﺴﺎﻟﯽ در دوره ﻫﺎي آﺗﯽ ﺑﻪ دﻟﯿﻞ ﮐﻤﺒﻮد تبخير - تعرق است . نتايج شاخص SPI ﻧﺸﺎن داد ﮐﻪ ﺷﺎﺧﺺ ﺧﺸﮑﺴﺎﻟﯽ در اﯾﻦ ﻣﻨﻄﻘﻪ در وﺿﻌﯿﺖ "ﺧﺸﮑﺴﺎﻟﯽ اوﻟﯿﻪ ﺑﻮد و در زﻣﺎن ﻫﺎي آتي نيز تغييري نيافت . ﻧﺘﯿﺠﻪ ﮔﯿﺮي: ﻧﺘﺎﯾﺞ ﺷﺎﺧﺺ ﻫﺎيSPI و ETDI ﺑﺴﯿﺎر ﺑﺎ ﻫﻢ ﺗﻔﺎوت داﺷﺖ .ﻋﻠﺖ آن ﻧﯿﺰ اﯾﻦ ﺑﻮد ﮐﻪ ﺧﺸﮑﺴﺎﻟي ﮐﺸﺎورزي ﺑﻪ ﮐﻤﺒﻮد ﺗﺒﺨﯿﺮ- ﺗﻌﺮق واﺑﺴﺘﻪ اﺳﺖ و ﺑﻪ ﻫﻤﯿﻦ دﻟﯿﻞ ﺷﺎﺧﺺ EDTI ﻧﺘﺎﯾﺞ ﺑﻬﺘﺮي ﺑﻪ دﺳﺖ داد .ﻣﻘﺎﯾﺴﻪ ﻧﺘﺎﯾﺞ ﺗﻔﺎوت زﯾﺎدي ﺑﯿﻦ اﯾﻦ دو ﺷﺎﺧﺺ ﺑﺎ اﺳﺘﻔﺎده از آﻣﺎره RMSE تفاوت زيادي در دوره هاي آتي نشان داد . علاوه بر اين ، شاخص ﻫﻤﺒﺴﺘﮕﯽ زﯾﺎدي ﻧﺴﺒﺖ ﺑﻪ ﻫﻢ (ﺑﺮ اﺳﺎس آﻣﺎره R2) ﻧﺪاﺷﺘﻨﺪ .وﺟﻮد اﯾﻦ ﺗﻔﺎوت ﻫﺎ ﻣﻨﻄﻘﯽ اﺳﺖ زﯾﺮا ﺷﺎﺧﺺ SPI از داده ﻫﺎي ﺑﺎرش و ﺷﺎﺧﺺ ETDI ازداده هاي ﺗﺒﺨﯿﺮ- ﺗﻌﺮق اﺳﺘﻔﺎده ﻣﯽ ﮐﻨﻨﺪ. ﺑﺮاﺳﺎس ﻧﺘﺎﯾﺞ اﯾﻦ ﭘﮋوﻫﺶ، ﺷﺎﺧﺺ SPIﻋﻨﻮان ﯾﮏ ﺷﺎﺧﺺ ﺑﺮاي ﺗﻌﯿﯿﻦ ﺧﺸﮑﺴﺎﻟﯽ ﮐﺸﺎورزي ﭘﯿﺸﻨﻬﺎد ﻧﻤﯽ ﺷﻮد.

Background and Objectives: Due to absolute dependence of agriculture on water, determine of drought condition in each region is very useful in planning the food sourcing. Unfortunately, there is no same definition about the “drought condition”, so there are some indexes to determine it. Standardized Precipitation Index (SPI) is one the meteorological indexes, which widely used to determine agricultural drought conditions. Evapotranspiration Deficit Index (ETDI) was also designed for this purpose. This index is used to determine agricultural drought conditions in arid and semi-arid region. Although there were most research about other drought indexes such as SPI, but there is few studies in oversea countries about use of ETDI index. Thus in this study tried to determine drought by ETDI and SPI indexes in Neyshabur plain by used of climate change models. Materials and Methods: This research was conducted to determine drought condition in Neyshabur plain located at longitude between 58˚ 13’-59˚ 30’ N and latitude between 35˚ 40’- 36˚ 39’ E, Iran. Evapotranspiration Deficit Index (ETDI) was developed based on weekly evapotranspiration deficit to determine drought condition in this region. In order to comparison of the ETDI results to other drought indices, we used Standardized Precipitation Index (SPI) as one the most common drought index. The data were collected from Neyshabur meteorological station for irrigated farms (wheat in Soleymani and Faroub farms, barley and corn) and rain-fed farms (rain-fed wheat) during 1992-2011. In order to estimate weather data for each index in the irrigated farms during two future periods (2020-2039 and 2080-2099), HADCM3, ECHOAM and CGCM3 T47 models were used based on A2, B1 and A1B scenarios and the climate model that has been used in rain-fed farm is the HADCM3 based on A2 and B1 scenarios. Root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) were used to comparison of the ETDI and SPI results. Results: Results showed that average ETDI were in initial wet condition for Faroub farm during base period (1992-2011) while it will be in drought condition during future periods (2020-2039 and 2080-2099). ETDI index was in normal condition for Soleymani farm during base period. Average ETDI indexes for these farms were in normal and initial dry condition during 2020-2039 and 2080-2099 periods, respectively. For barley and corn, ETDI indexes were in normal and initial dry condition during base period, respectively. This index was in normal statute for both of them during future periods. The ETDI value for rain-fed wheat was less compared to irrigated wheat during base period, although, this index will be increased during future periods. In most of scenarios, ETDI indexes showed negative values. It means that high drought condition will be happened during future periods due to deficit evapotranspiration. Results according to SPI index revealed that this region was in moderately drought condition and this situation will not change. Conclusion: High differences were obtained between ETDI and SPI results. Since agricultural drought depends on evapotranspiration deficits, ETDI is better index compared to SPI. The value of RMSE revealed poor adaptation between two indexes during future periods. In addition, ETDI were not correlated with SPI for all the scenarios in all scenarios. These differences are reasonable because SPI index only uses precipitation data and ETDI uses evapotranspiration. According to the results, it seems that SPI cannot be suggested as a good index in agricultural studies.