SPATIOTEMPORAL VARIATIONS IN THE IMPACTS OF URBAN LAND USE TYPES ON URBAN HEAT ISLAND EFFECTS: THE CASE OF RIYADH, SAUDI ARABIA

We explored the use of remote sensing for improving water use monitoring in agricultural areas by estimating evapotranspiration and validating it against smart field weighing lysimeter data. We found that Surface Energy Balance Algorithm for Land (SEBAL) was the most accurate approach for estimating actual evapotranspiration to help farmers understand crop water needs. Our results support smart tools in irrigation water management and monitoring with the aim to save the scarce water resources.

We developed and tested a conceptual model to estimate depression storage capacity (DSC) having small roughness values usually encountered in rainwater harvesting microcatchments in arid regions with only one fitting parameter. Results indicated that the developed linear model between DSC and the square root of the ration of random roughness (RR) to slope was significant. The model predicts depression storage of small relief at higher accuracy compared to other models found in the literature.