No abstract

Evapotranspiration (ET) estimation is important for water management decision tools. In this study, different ET data with varying resolution, accuracy, and functionality were reviewed over a semiarid, data-sparse region in southern Iran. Study results showed that the widely used reanalysis and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets have relatively high uncertainty and underestimated ET over the sparse heterogeneous landscape. On the other hand, fine-resolution ET datasets using Landsat imagery with Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Surface Energy Balance System (SEBS) algorithms, yielded high accuracy. Evaluation of METRIC and SEBS models in estimating seasonal crop water use showed a mean absolute error of 5% and 13%, respectively. The Satellite Application Facility on Climate Monitoring (CMSAF) data were used as radiation input to the models and were found to be a representative data source with daily average RMSE of 70 W m−2. An average crop coefficient Kc was estimated for the region and was obtained as 0.77. The study proposes and applies a hybrid framework that uses reference ET from simple diagnostic models (such as the REF-ET tool) and calculates actual ET by using the satellite-derived regionally and locally representative Kc values. The ET estimates generated with the framework were regionally representative and required low computational resources. The study findings have the potential to provide practical guidance to local farmers and water managers to generate useful and usable decision-making tools, especially for ET assessments in the study region and other data-sparse areas.

The Gareh Bygone Plain is an arid area, south of Zagros Mountains, in Southern Iran, where a floodwater spreading project has been implemented for artificial recharge of groundwater. Knowledge/mapping of actual evapotranspiration for the mainland uses (natural pasture, irrigated crops and tree plantations) is of major importance for water management in this remote area. The Surface Energy Balance System (SEBS) model was used to estimate actual evapotranspiration (ET) using non-cloudy images for 32 dates of Landsat 5 TM from May 2009 to October 2010. Various improvements were required for ET computations, including relative to the very high wind speed observed. Reference ET was computed with observed weather data and SEBS products. Thus, crop coefficients (Kc) were obtained as the ratios of actual to reference ET relative to the main types of vegetation. The mid-season Kc generated with SEBS were compared with those previously obtained in the region and with those published in literature. Consumed water by cultivated crops based on SEBS compared well with applied water measurements. Coherent results were obtained which allow validating the SEBS approach for conditions of limited available data

This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0-30, 30-60, and 60-90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0-30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 x 150 m(2)) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.