With an increasing demand of fresh water resources in arid/semi-arid parts of the world, researchers and practitioners are relying more than ever on remote sensing techniques for monitoring and evaluating crop water status and for estimating crop water use or crop actual evapotranspiration (ET_a). In this present study, infrared thermometry was used in conjunction with a few weather parameters to develop non-water-stressed and non-transpiring baselines for irrigated maize in a semi-arid region of Colorado in the western USA. A remote sensing-based Crop Water Stress Index (CWSI) was then estimated for four hourly periods each day during 5 August to 2 September 2011 (29 days). The estimated CWSI was smallest during the 10:00–11:00 a.m. and largest during the 12:00–13:00 p.m. hours. Plotting volumetric water content of the topsoil vs. CWSI revealed that there is a high correlation between the two parameters during the analyzed period. CWSI values were also used to estimate maize actual transpiration (T_a). T_a estimates were more influenced by crop biomass rather than irrigation depths alone, mainly due to the fact that the effects of deficit irrigation were largely masked by the significant precipitation during the growing season. During the study period, applying an independent remotely sensed energy balance model showed that maize ET_a was 159 mm, 30% larger than CWSI-T_a (122 mm) and 9% smaller than standard-condition maize ET (174 mm).

Optical and thermal remote sensing data were acquired at ground level over several turfgrass species under different soil and irrigation treatments in northern Colorado, USA. Three vegetation indices (VIs), estimated based on surface spectral reflectance, were sensitive to the effect of reduced water application on turfgrass quality. The temperature-based Grass Water Stress Index (GWSI) was also estimated by developing non-transpiring and non-water-stressed baselines. The VIs and the GWSI were all consistent in (i) having a non-linear relationship with the water application depth; and, (ii) revealing that the sensitivity of studied species to water availability increased in order from warm season mix to Poa pratensis L. and then Festuca spp.. Implemented soil preparation treatments had no significant effect on turfgrass quality and water stress. The differences between GWSI-based estimates of water use and the results of a complex surface energy balance model (METRIC) were not statistically significant, suggesting that the empirical GWSI method could provide similar results if the baselines are accurately developed under the local conditions of the study area.

A research project was carried out to estimate daily crop water stress index (CWSI) of corn, planted in NE Colorado under limited irrigation practice. In CWSI estimation, required weather/canopy parameters were measured every day between 1200 and 1300 hours, while the upper and lower limits of air-canopy temperature differential (dT) were identified by applying several previously-developed methods. A simple approach for checking the accuracy of implemented dT limits was proposed. In addition, corn actual evapotranspiration (ET) was estimated by combining resulted CWSI values with corn potential ET, calculated using the data collected at a nearby weather station. Despite a significant variation among them, all of the implemented methods for identifying upper and lower dT limits resulted in a corn ET lower than its potential rate, indicating that CWSI approach can effectively detect the existence of water stress in corn. The differences among applied methods could be attributed to the differences in agro-climatic conditions under which they were developed.