Allowing the Actual Evapotranspiration Uncertainty in Hydrological Models: Coupling of Interval-Based Water Balance and METRIC Models

Against the paramount role of actual evapotranspiration (ET) in hydrological modeling, determining its values is mixed with different sources of uncertainties. In addition, estimation of ET with energy-based methods (e.g., METRIC) leads to different results with various acceptable initial and boundary conditions (such as land use and cold/hot pixels). The aim of the current research is to allow the uncertainty effects of ET as an interval-based input variable in hydrological modeling. The goal is achieved via feeding the uncertainty of computed ET values to the developed Interval-Based Water Balance (IBWB) model in terms of gray values. To this purpose, the comprehensive monthly water balance model (including surface and groundwater modules) has been revised to a new interval-based form. Moreover, the METRIC model has been used 20 times in each month of computational period to calculate the ET patterns with different hot/cold pixels to provide monthly ensemble ET values. For a comprehensive assessment, the selected water balance model has been calibrated with ensemble means of the computed ET with its classical type. The study area is a mountainous sub-basin of the Sefidrood watershed, Ghorveh-Dehgolan basin, with three alluvial aquifers in the North of Iran. Not only the paradigm shift from determinist to interval-based hydrologic structure improved the statistical metrics of the models’ responses, but also it decreased the uncertainty of the simulated streamflow and groundwater levels.

Estimating Actual Evapotranspiration over Croplands Using Vegetation Index Methods and Dynamic Harvested Area

Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVIMccL and EVI2MccL) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.

Evapotranspiration measurements in the Brazilian Caatinga dry forest

<p>The Brazilian semiarid region (one million km²) is densely populated (25 million inhabitants), but its natural water availability is low. Despite the fact that evaporative processes are key to the regional water deficit, the actual evapotranspiration of natural environment has rarely been measured, especially in the native Caatinga dry forest. We hereby propose a simple method that demands the monitoring of five meteorological variables: relative humidity, global radiation, canopy and air temperature, as well as wind speed. These values are used to assess leaf energy balance, yielding net radiation (Rn) and actual evapotranspiration (LE). To estimate the actual Caatinga evapotranspiration under natural conditions and in different seasons, the proposed method was applied <em>in situ</em> during nine months. The application site was the Aiuaba Experimental Basin, situated in an environmental protection area in the North-eastern Brazil. The method provided consistent results when compared with independent measurements, such as atmospheric demand, leaf area, and soil water content variation. Results indicate that the daily average net radiation is 12 MJ m<sup>-</sup>². During the dry season, the actual evapotranspiration is very low, with negligible LE/Rn ratio. Contrastingly, in the rainy season, it raises to 6 mm per day, with average LE/Rn ratio equalling 0.89. The results show that the actual evapotranspiration in the Caatinga long-lasting dry season (up to nine months per year) is controlled by the water availability in the soil.</p>

Spatial and Temporal Resolution Improvement of Actual Evapotranspiration Maps Using Landsat and MODIS Data Fusion

Producing daily actual evapotranspiration (ETa) maps with high spatial resolution has always been a challenge for remote sensing research. This study assessed the feasibility of producing daily ETa maps with a high spatial resolution (30 m) for the sugarcane farmlands of Amir Kabir Sugarcane Agro-industry (Khuzestan, Iran) using three different scenarios. In the first scenario, the reflectance bands of Landsat 8 were predicted from the moderate resolution imaging spectroradiometer (MODIS) imagery using the spatial and temporal adaptive reflectance fusion model (STARFM) algorithm. Also, the thermal bands of Landsat 8 were predicted by the spatiotemporal adaptive data fusion algorithm for temperature mapping (SADFAT). Then, ETa amounts were calculated employing such bands and the surface energy balance algorithm for land (SEBAL). In the second scenario, the input data needed by SEBAL were downscaled using the MODIS images and different methods. Then, using the downscaled data and SEBAL, daily ETa amounts with a spatial resolution of 30 m were calculated. In the third scenario, ETa data acquired by MODIS were downscaled to the scale of Landsat 8. In the second and third scenarios, downscaling of the data was carried out by the ratio, regression, and neural networks methods with two different approaches. In the first approach, the Landsat image on day 1 and the relationship between the two MODIS images on day 1 and the other days were used. In the second approach, the simulated image on the previous day and the relationship between the two consecutive images of MODIS were used. Comparing the simulated ETa amounts with the ETa amounts derived from Landsat 8, the first scenario had the best result with an RMSE (root mean square error) of 0.68 mm day−1. The neural networks method used in the third scenario with the second approach had the worst result with an RMSE of 2.25 mm day−1, which was however a better result than the ETa amounts derived from MODIS with an RMSE of 3.19 mm day−1. The method developed in this study offers an efficient and inexpensive way to produce daily ETa maps with a high spatial resolution. Furthermore, we suggest that STARFM and SADFAT algorithms have acceptable accuracies in the simulation of reflectance and thermal bands of Landsat 8 images for homogeneous areas.

Comparative Evaluation of Simplified Surface Energy Balance Index-Based Actual ET against Lysimeter Data in a Tropical River Basin

In the past decades, multispectral and multitemporal remote sensing has been popularly used for estimating actual evapotranspiration (ETc) across the globe. It has been proven to be a cost-effective tool for understanding agricultural practices in a region. Today, because of the availability of different onboard sensors on an increasing number of different satellites, land surface activity can be captured at fine spatial and time scales. In the present study, three multi-date satellite imageries were used for the evaluation of remote sensing-based estimation of actual evapotranspiration in paddy in the command area of the tropical Kangsabati river basin. A surface energy balance model, the Simplified-Surface Energy Balance Index (S-SEBI), was applied for all three dates of the Rabi season (2014–2015) for the estimation of actual evapotranspiration. The crop coefficient was calculated using the exhaustive survey data collected from the command area and adjusted to local conditions. The ETc estimated using the S-SEBI-based model was compared with the Food and Agriculture Organization Penman–Monteith (FAO-56 PM) method multiplied by the adjusted local crop coefficient and lysimeter data in the command area. The coefficient of determination (r2) was applied to examine the accuracy of the S-SEBI model with respect to lysimeter data and the FAO-56 PM-based ETc. The results showed that the S-SEBI model performed well with the lysimeter (r2 = 0.90) in comparison with FAO-56 PM, with an r2 of 0.65. In addition to this, the S-SEBI-based ET estimates correlated well with the FAO-56 PM, with r and RMSE values of 0.06 and 1.13 mm/day (initial stage), 0.85 and 0.48 mm/day (development stage), and 0.77 and 0.52 (maturity stage) for paddy, respectively. The S-SEBI-based ETc estimate varied with different stages of crop growth and successfully captured the spatial heterogeneity within the command area. In general, this study showed that the S-SEBI method has the potential to calculate spatial evapotranspiration and provide useful information for efficient water management. The results revealed the applicability and accuracy of remote sensing-based ET for managing water resources in a command area with scarce data.

Calibration and Validation of AQUACROP and APSIM Models to Optimize Wheat Yield and Water Saving in Arid Regions

The APSIM-Wheat and AQUACROP models were calibrated for the Sakha 95 cultivar using phenological data, grain and biomass yield, and genetic parameters based on field observation. Various treatments of planting dates, irrigation, and fertilization were applied over the two successive winter growing seasons of 2019/2020 and 2020/2021. Both models simulated anthesis, maturity dates, grain yield, and aboveground biomass accurately with high performances (coefficient of determination, index of agreement greater than 0.8, and lower values of root mean square deviation) in most cases. The calibrated models were then employed to explore wheat yield and water productivity (WP) in response to irrigation and nitrogen fertilization applications. Scenario analyses indicated that water productivity and yield of wheat ranged from 1.2–2.0 kg m–3 and 6.8–8.7 t ha–1, respectively. Application of 0.8 from actual evapotranspiration and 120% from recommended nitrogen dose was the best-predicted scenario achieving the highest value of crop WP. Investigating the suitable option achieving the current wheat yield by farmers (7.4 t ha–1), models demonstrated that application of 1.4 from actual evapotranspiration with 80% of the recommended nitrogen dose was the best option to achieve this yield. At this point, predicted WP was low and recorded 1.5 kg m–3. Quantifying wheat yield in all districts of the studied area was also predicted using both models. APSIM-Wheat and AQUACROP can be used to drive the best management strategies in terms of N fertilizer and water regime for wheat under Egyptian conditions.