Browsing by Author "Fares, Ali"
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Item Estimating reference crop evapotranspiration under limited climate data in West Texas(2020) Awal, Ripendra; Habibi, Hamideh; Fares, Ali; Deb, Sanjit (TTU)Study region: West Texas, USA Study focus: Estimation of crop reference evapotranspiration (ETo) is essential for many aspects of water resources planning and management such as irrigation scheduling. Available widely used methods for calculating ETo include American Society of Civil Engineers’ Standardized Reference Evapotranspiration and Food and Agriculture Organization's Penman-Monteith equations (FAO-ETo). These methods use complete climate datasets to estimate daily ETo, whereas simple evapotranspiration models based on radiation and temperature use limited climate data. In this study, daily ETo estimated using the temperature based Hargreaves-Samani (HS) equation were compared and evaluated with those estimated using the standard FAO-ETo at different stations of West Texas Mesonet. New hydrological insights for the region: The results showed that the HS equation with original coefficients underestimated daily ETo values as compared to FAO-ETo data. New coefficients of the globally, monthly and regionally calibrated HS equation against FAO-ETo data were derived and proposed for more accurate daily ETo estimates in West Texas. Based on the results of global, monthly and regional calibration scenarios, ETo estimated by the calibrated and validated HS equation using fitted month-specific coefficients showed better agreement with FAO-ETo both within and outside the calibration region. No significant improvement in ETo estimation was observed for the HS equation using interpolated coefficients derived from station-specific calibrated coefficients as compared with commonly calibrated coefficients derived based on datasets of all selected meteorological stations in West Texas.Item Soil physical properties spatial variability under long-term no-tillage corn(2019) Awal, Ripendra; Safeeq, Mohammad; Abbas, Farhat; Fares, Samira; Deb, Sanjit K. (TTU); Ahmad, Amjad; Fares, AliSpatial variability of soil physical and hydrological properties within or among agricultural fields could be intrinsically induced due to geologic and pedologic soil forming factors, but some of the variability may be induced by anthropogenic activities such as tillage practices. No-tillage has been gaining ground as a successful conservation practice, and quantifying spatial variability of soil physical properties induced by no-tillage practices is a prerequisite for making appropriate site-specific agricultural management decisions and/or reformulating some management practices. In particular, there remains very limited information on the spatial variability of soil physical properties under long-term no-tillage corn and tropical soil conditions. Therefore, the main objective of this study was to quantify the spatial variability of some selected soil physical properties (soil surface temperature (ST), volumetric water content (θv), soil resistance (TIP), total porosity (θt), bulk density (ρb), organic carbon, and saturated hydraulic conductivity (Ksat)) using classical and geostatistical methods. The study site was a 2 ha field cropped no-tillage sweet corn for nearly 10 years on Oahu, Hawaii. The field was divided into 10 × 10 and 20 × 20 m grids. Soil samples were collected at each grid for measuring ρb, θt, and soil organic carbon (SOC) in the laboratory following standard methods. Saturated hydraulic conductivity, TIP at 10 and 20 cm depths, soil surface temperature, and θv were also measured. Porosity and ρb have low and low to moderate variability, respectively based on the relative ranking of the magnitude of variability drawn from the coefficient of variation. Variability of the SOC, TIP, and Ksat ranges from moderate to high. Based on the best-fitted semivariogram model for finer grid data, 9.8 m and 142.2 m are the cut off beyond which the measured parameter does not show any spatial correlation for SOC, and TIP at 10 cm depth, respectively. Bulk density shows the highest spatial dependence (range = 226.8 m) among all measured properties. Spatial distribution of the soil properties based on kriging shows a high level of variability even though the sampled field is relatively small.