Use of thermal and visible imagery for estimating crop water status of irrigated grapevine

Achieving high quality wine grapes depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. This study investigates the use of thermal imaging for monitoring water stress. Experiments were conducted on a wine-grape (Vitis vinifera cv. Merlot) vineyard in northern Israel. Irrigation treatments included mild, moderate, and severe stress. Thermal and visible (RGB) images of the crop were taken on four days at midday with a FLIR thermal imaging system and a digital camera, respectively, both mounted on a truck-crane 15 m above the canopy. Aluminium crosses were used to match visible and thermal images in post-processing and an artificial wet surface was used to estimate the reference wet temperature (T(wet)). Monitored crop parameters included stem water potential (Psi(stem)), leaf conductance (g(L)), and leaf area index (LAI). Meteorological parameters were measured at 2 m height. CWSI was highly correlated with g(L) and moderately correlated with Psi(stem). The CWSI-g(L) relationship was very stable throughout the season, but for that of CWSI-Psi(stem) both intercept and slope varied considerably. The latter presumably reflects the non-direct nature of the physiological relationship between CWSI and Psi(stem). The highest R(2) for the CWSI to g(L) relationship, 0.91 (n=12), was obtained when CWSI was computed using temperatures from the centre of the canopy, T(wet) from the artificial wet surface, and reference dry temperature from air temperature plus 5 degrees C. Using T(wet) calculated from the inverted Penman-Monteith equation and estimated from an artificially wetted part of the canopy also yielded crop water-stress estimates highly correlated with g(L) (R(2)=0.89 and 0.82, respectively), while a crop water-stress index using 'theoretical' reference temperatures computed from climate data showed significant deviations in the late season. Parameter variability and robustness of the different CWSI estimates are discussed. Future research should aim at developing thermal imaging into an irrigation scheduling tool applicable to different crops.     

Climatic and hydrological aspects of the Hula restoration project

Drying the Hula marshes (northern Israel) in the 1950s caused changes in sub-surface hydrology that severely compromised agricultural sustainability of the Hula Valley peatlands. The complex dynamics between climatic and hydrological regimes produced widely fluctuating elevations in the water table, leading to deterioration of the peat soils through enhanced aerobic decomposition, wind erosion, and underground fires. The year-round intensive and diverse cropping systems used in 1960s were gradually replaced in the 1980s by extensive winter forage crops, leaving the peat uncropped and exposed to increased deterioration in the dry season. The Hula Restoration Project was initiated in 1993 to moderate some of these after-effects of the draining of the Hula marshes. The project includes a 90-km network of water-level regulating supply and drainage canals and a 100-ha lake and a barrier to underground water flow from the lake to cultivated areas. We followed changes in underground water levels for the five years before and the three years after re-flooding of the valley in May 1994. Prior to re- flooding, water tables in the area fluctuated 2–4 m annually, depending on location and microrelief and there was a strong north to south flow of water. After re-flooding the lake initially had a strong influence on water table elevation in the adjacent areas, which later stabilized. The underground barrier shifted the predominant water flow westward toward a north-south canal near the edge of the valley and then southward along the canal. The restoration project has been successful up to now, there are few underground fires since re-flooding, and all agricultural lands can be cultivated al year long.     

The management of Lake Agmon Wetlands (Hula Valley,Israel)

Hydrobiologia - Lake Hula and its surrounding swamps were drained in the 1950s. Forty years later a draw down of groundwater table and peat soils degradation resulted in damage to agricultural...     

Estimation of leaf water potential by thermal imagery and spatial analysis

Canopy temperature has long been recognized as an indicator of plant water status and as a potential tool for irrigation scheduling. In the present study, the potential of using thermal images for an in-field estimation of the water status of cotton under a range of irrigation regimes was investigated. Thermal images were taken with a radiometric infrared video camera. Specific leaves that appeared in the camera field of view were sampled, their LWP was measured and their temperature was calculated from the images. Regression models were built in order to predict LWP according to the crop canopy temperature and to the empirical formulation of the crop water stress index (CWSI). Statistical analysis revealed that the relationship between CWSI and LWP was more stable and had slightly higher correlation coefficients than that between canopy temperature and LWP. The regression models of LWP against CWSI and against leaf temperatures were used to create LWP maps. The classified LWP maps showed that there was spatial variability in each treatment, some of which may be attributed to the difference between sunlit and shaded leaves. The distribution of LWP in the maps showed that irrigation treatments were better distinguished from each other when the maps were calculated from CWSI than from leaf temperature alone. Furthermore, the inclusion of the spatial pattern in the classification enhanced the differences between the treatments and was better matched to irrigation amounts. Optimal determination of the water status from thermal images should be based on an overall view of the physical status as well as on the analysis of the spatial structure. Future study will involve investigating the robustness of the models and the potential of using water status maps, derived from aerial thermal images, for irrigation scheduling and variable management in commercial fields.