Eyüp Selim Köksal

Irrigation water management with water deficit index calculated based on oblique viewed surface temperature

In this study, the relationship between water deficit index (WDI) and a number of parameters related to soil water status, crop monitoring and yield were investigated with regard to drip irrigated dwarf green beans (Phaseolus vulgaris, humilis) in Ankara, Turkey during the 2004 and 2005 growing seasons. Three different WDIs were calculated based on three different spectral indexes and oblique viewed surface temperature. Soil water status was quantified by soil water content (SWC) and soil water deficit index (SWDI). Crop evapotranspiration (ETc), leaf water potential (LWP), spectral indexes and crop water stress index (CWSI) were determined. Although the WDIs have statistically significant relationships with the parameters, it is hard to use WDIs based on oblique viewed surface temperature for irrigation scheduling purposes. However, total yield estimation and monitoring of seasonal crop water use status could be achieved through this kind of WDI.

Predicting field capacity, wilting point, and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches

In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R2), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P < 0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP = 0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.

Evaluation of spectral vegetation indices as an indicator of crop coefficient and evapotranspiration under full and deficit irrigation conditions

Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ET c) were observed. Daily ET c values were calculated based on energy balance and soil water balance residual. The fraction of reference ET (ETrF), which is essentially the same with the crop coefficient (K c), was determined, and relationships between spectral vegetation indices (SVIs) were analysed. Under water stress conditions, the ET c and ETrF values estimated by means of energy balance were relatively high. In order to improve the correlation between ETrF and SVIs and for correction of ET c for water‐stressed irrigation treatments, a modification ratio was calculated based on SVIs. Although all three SVIs have a significant relationship with ETrF, the correctness of the modification with a Simple Ratio (SR) was higher. As a consequence, ETrF or crop coefficient (K c) could be estimated by SR, and this information could be used for irrigation water management of large‐scale agricultural lands.

ŞEKER PANCARI SULAMA ZAMANI BELİRLENMESİNDE BİTKİ SU STRES İNDEKSİNİN KULLANILMA OLANAKLARI

Su kaynaklarinin surdurulebilir kullanilmasinda sulama suyu yonetimi buyuk oneme sahiptir. Diger yandan suyun tarlada uygulanmasi sulama suyu yonetiminde basariyi belirleyici bir unsurdur. Gerektigi zamanda yeterli miktarda sulama temel yaklasim olarak kabul edilebilir. Bu nedenle sulamaya karar vermede destek araclari giderek onem kazanmaktadir. Bu calismada son yillarda teknolojik gelismeler sayesinde one cikan bitki su stres indeksinin (CWSI), ulkemizde sulama suyunun cok yogun bir bicimde uygulandigi seker pancari bitkisinde kullanilma olanaklari arastirilmistir. Bu amacla yedi farkli sulama konusundan olusan seker pancari denemesi Ankara kosullarinda agir bunyeli toprakta, 2004 ve 2005 yillarinda yurutulmustur. Her bir deneme konusunda yetisme donemi boyunca bitki ortu sicakligi izlenmistir. Es zamanli olarak hava sicakligi ve buhar basinci acigina (VPD) iliskin iklim elemanlari olculmustur. Calisma sonucunda seker pancari bitkisine iliskin CWSI hesabinda kullanilan alt baz ve ust baz hatlari deneysel olarak tespit edilmistir. Buna gore hesaplanan CWSI degerleri konular arasindaki sulama suyu farkliligini ortaya koymustur. Sonuc olarak CWSI’ nin seker pancari sulama suyu yonetiminde etkili bir bicimde kullanilabilecegi degerlendirilmistir. Irrigation water management is one of the most important steps of sustainable use of water resources. On the other hand, field application of water is a critical component which affects the achievement of irrigation water management. The fundamental principal is application of irrigation at correct time and enough amounts. Because of this, decision tools for irrigation have become very important. In this study, the use of crop water stress index (CWSI), which have very popular in recent years as a result of technological developments, was investigated for irrigation timing in sugar beet cultivation, which is very intensively irrigated crop in Turkey. For this purpose, field trials consisting of seven different irrigation treatments were applied under Ankara climatic and heavy soil conditions during the growing seasons of 2004 and 2005. Crop canopy temperature was monitored for each irrigation treatments separately. Air temperature and components of vapor pressure deficit (VPD) were measured, simultaneously. Lower and upper limits of basic graphic, which is necessary for CWSI calculation, were determined for sugar beet. CWSI values calculated using these lines determined the difference among irrigation applications. As a result, it was shown that CWSI could be used for management of sugar beet irrigation water effectively.