پایش رطوبت خاک در مراحل رشد گندم دیم به کمک نمایه‌های هواشناسی و سنجش از دور

در ایران به دلیل کمبود داده های رطوبت اعماق خاک با توزیع مکانی مناسب، تحقیقات مرتبط با خشکسالی کشاورزی و پایش رطوبت خاک نسبت به خشکسالی از نوع هواشناسی و آب شناسی کمتر انجام شده است. هدف اصلی از تحقیق حاضر پایش رطوبت خاک در اعماق 10 ، 20، 30، 40، 50 و 70 سانتی متری به کمک داده های زمینی و سنجش از دور در مراحل رشد گندم دیم (جوانه زنی تا 4 برگی، ساقه دهی و شکم پر تا رسیدگی کامل) در شهرستان نیشابور بوده است. اثر نوسانات رطوبت خاک روی عملکرد گندم دیم در مراحل رشد نیز مورد بررسی قرار گرفته است. به همین منظور تاریخ های دیدبانی شده مراحل رشد گندم دیم در ایستگاه تحقیقات هواشناسی کشاورزی نیشابور طی سال های زراعی 1390-1389 تا 1393-1392 و متغیرهای هواشناسی به همراه نمایه های spi، spei، ndvi، vci و tci مورد استفاده قرار گرفتند. نتایج نشان دادند که تنها رطوبت عمق 10 سانتی متری خاک با نمایه های ndvimax (r=0.595) و spei (r=0.780) ارتباط معنی دار داشته است. براساس نتایج به دست آمده، 35 و 61 درصد تغییرات رطوبت عمق 10 سانتی متری خاک به ترتیب به کمک ndvimax و spei قابل توجیه بوده است. در خصوص تغییرات عملکرد گندم دیم با رطوبت اعماق خاک هر چند روابط معنی داری حاصل نشد، اما نتایج بیانگر اهمیت بارش های فروردین ماه در نوسانات رطوبت خاک و متعاقب آن عملکرد گندم دیم در نیشابور می باشد. در پایان می توان نمایه هایndvimax  و spei را به دلیل ماهیت ذاتی مولفه های دخیل در محاسبه آن ها، به عنوان سنجه های پایش رطوبت خاک معرفی نمود.

Monitoring soil moisture at the growth stages of rain-fed wheat using meteorological and remote sensing indices

Introduction Drought has a huge impact on crop production. Therefore, a better understanding of drought and other atmospheric phenomena is important in order to reduce the damage caused by them. In Iran, most of the studies related to agricultural drought is carried out using remote sensing data due to the lack of insitu soil moisture data. In fact, because of shortage of soil moisture data alongside a reasonable spatial distribution across the country, the researches pertaining to agricultural drought have been conducted less comparing to meteorological and hydrological drought. However, a few attempts were made to monitor agricultural drought by some researchers in Iran. This study aimed to monitor soil moisture at different depths using insitu together with remotelysensed data in Neyshabur City. In addition, the impact of soil moisture on rainfed wheat yield in different crop growth stages was investigated.Materials and MethodsNeyshabur city with an area of 869843.23 ha is extended from center to northwest of Khorasan Razavi province. It is in the neighborhood of Torbat Heydariyeh and Kashmar counties from the south, Sabzevar from the west, Faroj and Quchan from the north and Mashhad and Chenaran from the east. Its’ geographical location ranges from 35° 30 ʹ to 36° 59ʹ N latitudes and 57° 40ʹ to 59° 30 ʹ E longitudes. Farmers cultivate rainfed wheat in early November and harvest it in late June. The observed data of rainfed wheat growth stages from Neyishabur agrometeorological research station of 20102011 to 20142014 were used. The start and end dates of wheat growth stages of Sardari cultivar, together with measured biometric variables were used for further statistical analysis.In addition, measured soil moisture was used at different depths of 10, 20, 30, 40, 50 and 70 cm, in a weekly base during 20102011 to 20132014. To investigate the impact of meteorological variables on wheat yield, the drought indices, including Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were calculated. Moreover, remotelysensed based indices, including Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) were derived from different bandwidths of TM, ETM+ and OLI sensors of Landsat satellite. Statistical analysis was performed using Pearson correlation coefficient to find out the correlation among variables. Besides, the simple regression analysis was carried out to calculate the relationship between soil moisture at different depths and meteorological and remote sensing indices. The impact of soil moisture on rainfed wheat yield was investigated using statistical regression analysis. The statistical analysis was carried out for three wheat growth stages including primary stage (from germination to four leaf), intermediate stage (from tillering to stem elongation) and final growth stage (from booting to physiological maturity).Results and DiscussionThe results revealed that the maximum and minimum NDVI values during December (germination and four leaf growth stages) were 0.769 and 0.355 in 201112 and 201011, respectively. It is interesting that wheat yield was 1645 and 3845 kg/ha in 201011 and 201112, respectively, which correspond to mentioned NDVI values. In addition, the maximum and minimum range of NDVI variations for whole growing season were for 201314 and 201112 with maximum and minimum wheat yield, respectively (3845 and 1645 kg/ha). Therefore, it could be partly due to appropriate temporal distribution of precipitation and partly because of adequate soil moisture at crop root zone at germination and four leaf growth stages.The statistical regression analysis showed that soil moisture in 10 cm depth had a significant positive correlation with NDVImax and SPEI, with correlation coefficients of 0.595 and 0.780, respectively. In other words, 35 and 61 percent of variations of 10 cm soil moisture depth were accounted for NDVImax and SPEI, respectively. The results showed that, the relationship between rainfed wheat yield and soil moisture depths was nonsignificant at different crop growth stages. Although, it should be noted that the April precipitation was important for soil moisture variations and consequently for rainfed wheat yield. It coincided with start of booting stage of crop.ConclusionsThe results of this study revealed that NDVImax and SPEI had the most significant correlations with soil moisture at 10 cm depth. However, no significant relationships were found among soil moisture at 20, 30, 40, 50, and 70 cm depths with meteorological and remote sensing indices.