Evapotranspiration Parameters Research Articles

Performance fuzzy analytical hierarchy process to identify drought areas for disaster mitigation

Drought causes crop failure in the agricultural sector and a limited supply of clean water. Land damage due to drought in Lamongan has reached ±12,000 ha in the last decade. The lack of information regarding drought disaster mitigation resulted in quite large losses in several agricultural sectors. The purpose of this study is to develop a decision support system (DSS) that can provide information regarding the identification of drought-prone areas. The fuzzy analytical hierarchy process (FAHP) method is implemented with four criteria: rainfall intensity, slope, soil type, and distance to the river. FAHP is good for processing the weighting of several criteria and categories to produce good choices. Results, the tests carried out there were 20 sub-districts prone to drought, with an accuracy rate of the FAHP method of 85%. The average value of respondent satisfaction averaged 97.2%. DSS application can provide the status of areas prone to drought. For future studies, the temperature and evapotranspiration parameters can be added, to provide better results.

Calibration of Land-Use-Dependent Evaporation Parameters in Distributed Hydrological Models Using MODIS Evaporation Time Series Data

The land-use-specific calibration of evapotranspiration parameters in hydrologic modeling is challenging due to the lack of appropriate reference data. We present a MODIS-based calibration approach of vegetation-related evaporation parameters for two mesoscale catchments in western Germany with the physically based distributed hydrological model WaSiM-ETH. Time series of land-use-specific actual evapotranspiration (ETa) patterns were generated from MOD16A2 evapotranspiration and CORINE land-cover data from homogeneous image pixels for the major land-cover types in the region. Manual calibration was then carried out for 1D single-cell models, each representing a specific land-use type based on aggregated 11-year mean ETa values using SKout and PBIAS as objective functions (SKout > 0.8, |PBIAS| < 5%). The spatio-temporal evaluation on the catchment scale was conducted by comparing the simulated ETa pattern to six daily ETa grids derived from LANDSAT data. The results show a clear overall improvement in the SPAEF (spatial efficiency metric) for most land-use types, with some deficiencies for two scenes in spring and late summer due to phenological variation and a particularly dry hydrological system state, respectively. The presented method demonstrates a significant improvement in the simulation of ETa regarding both time and spatial scale.

Spatio-temporal sensitivity analysis of the wetland modules of a semi-distributed hydrological model

Hydrological models offer the opportunity to evaluate wetland conservation networks as nature-based solutions to mitigate hydrological extremes. To optimize the replication of a hydrological model response (i.e., stream flows), the models rely on input data (land cover, hydrographic network, soil types, topography, meteorological data) and parameters. However, the effect of parametric uncertainty on the simulated variables and the spatio-temporal variability of this sensitivity are insufficiently documented. This study presents an application of the novel global sensitivity analysis method, the Variogram Analysis of Response Surface, to the isolated and riparian wetland modules of HYDROTEL, a semi-distributed, process-based, deterministic model, on two watersheds located in the province of Quebec, Canada. The analysis accounted for: (i) the spatial variability by assessing the sensitivity at various locations in the watersheds and by compiling sensitivity indices for wetland networks discretized following the Strahler order classification which quantifies the structure of hydrographic networks and (ii) the temporal variability of the sensitivity using the Generalized Global Sensitivity Matrix. The results indicate that the parameters defining the geometry of wetlands (area, depth) are the most sensitive for both isolated and riparian wetlands, and for all Strahler orders. The temporal assessment of sensitivity highlights the seasonal controlling processes, including a peaking sensitivity of the maximum water depth in wetlands during spring snowmelt, whereas the sensitivity of the evapotranspiration parameter increases during summer, but is null during winter. Results also indicate that the parameters of the isolated modules are more sensitive for wetlands located on lower stream order (upstream/headwaters) while those of the riparian modules display a greater sensitivity when wetlands are located on higher Strahler orders (downstream/main channel). These findings deepen our understanding of the impact of wetland features on stream flows and provide guidelines to plan future data acquisition campaigns in wetlandscapes.

Determination of the Evapotranspiration Parameters of Benin City Based on the Penman-Monteith Equation from 1979 to 2013

Determination of the Evapotranspiration Parameters of Benin City Based on the Penman-Monteith Equation from 1979 to 2013

Евапотранспірація та врожайність соняшнику і нуту за краплинного зрошення

Goal. Set the parameters of irrigation regimes, evapotranspiration (ETc) and crop and chickpea yields depending on the designs of drip irrigation systems and water supply regime. Methods. Shortterm field experiments, analytical and statistical methods of experimental data processing. The results. It has been proven that the method of laying irrigation pipelines of drip irrigation systems significantly affects the parameters of evapotranspiration, the water regime, and the yield of sunflower and chickpea in the conditions of the Dry Steppe. Thus, sunflower evapotranspiration parameters were at the level of 2,94–3,05 thousand m3/ha in non-irrigated conditions, 4,36–4,62 thousand m3/ha with underground placement of irrigation pipelines (at a depth of 0,3 m) and 4,73–5,24 thousand m3/ha for the above-ground placement of irrigation pipelines. The same parameters for growing chickpeas were: 3,15 thousand m3/ha in non-irrigated conditions, 5,47–5,76 thousand m3/ha under subsoil drip irrigation and 6,23–6,99 thousand m3/ha — for the above-ground placement of irrigation pipelines. The amount of evapotranspiration when implementing the pulse water supply regime was 4,85 thousand m3/ha and 5,69 thousand m3/ha for sunflower and chickpea, respectively. Conclusions. The introduction of subsurface drip irrigation is more appropriate for the cultivation of sunflower and chickpea, which is explained by their drought resistance. The variant with subsurface laying of irrigation pipelines of drip irrigation provided almost identical yield parameters with lower plant water consumption coefficients. Thus, the minimum water consumption coefficients (1077,8 m3/t — sunflower, 1329,7 m3/t — chickpea) were obtained under the condition of implementation of the pulse water supply mode. The same version of the experiment provided the highest level of crop yield — 4,50 t/ha for growing sunflowers and 4,28 t/ha for chickpeas.

Daily actual evapotranspiration estimation of different land use types based on SEBAL model in the agro-pastoral ecotone of northwest China.

Evapotranspiration (ET) plays a crucial role in hydrological and energy cycles, as well as in the assessments of water resources and irrigation demands. On a regional scale, particularly in the agro-pastoral ecotone, clarification of the distribution of surface ET and its influencing factors is critical for the rational use of water resources, restoration of the ecological environment, and protection of ecological water sources. The SEBAL model was used to invert the regional ET based on Landsat8 images in the agro-pastoral ecotone of northwest China. The results were indirectly verified by monitoring data from meteorological stations. The correlation between ET and surface parameters was analyzed. Thus, the main factors that affect the surface ET were identified. The results show that the SEBAL model determines an accurate inversion, with a correlation coefficient of 0.81 and an average root mean square error of 0.9 mm/d, which is highly suitable for research on water resources. The correlation coefficients of normalized vegetation index, surface temperature, land surface albedo, net radiation flux with daily ET were 0.5830, 0.8425, 0.3428 and 0.9111, respectively. The normalized vegetation index and the net radiation flux positively correlated with the daily ET, while the surface temperature and land surface albedo negatively correlated with the daily ET. The correlation from strong to weak is the net radiation flux > surface temperature > normalized vegetation index > surface albedo. In terms of spatial distribution, the daily ET of water was the highest, followed by woodland, wetland, cropland, built-up land, shrub land, grassland and bare land. However, the SEBAL model overestimates the inversion of daily ET of built-up land.

Assessing Daily Evapotranspiration Methodologies from One-Time-of-Day sUAS and EC Information in the GRAPEX Project.

Daily evapotranspiration (ETd) plays a key role in irrigation water management and is particularly important in drought-stricken areas, such as California and high-value crops. Remote sensing allows for the cost-effective estimation of spatial evapotranspiration (ET), and the advent of small unmanned aerial systems (sUAS) technology has made it possible to estimate instantaneous high-resolution ET at the plant, row, and subfield scales. sUAS estimates ET using “instantaneous” remote sensing measurements with half-hourly/hourly forcing micrometeorological data, yielding hourly fluxes in W/m2 that are then translated to a daily scale (mm/day) under two assumptions: (a) relative rates, such as the ratios of ET-to-net radiation (Rn) or ET-to-solar radiation (Rs), are assumed to be constant rather than absolute, and (b) nighttime evaporation (E) and transpiration (T) contributions are negligible. While assumption (a) may be reasonable for unstressed, full cover crops (no exposed soil), the E and T rates may significantly vary over the course of the day for partially vegetated cover conditions due to diurnal variations of soil and crop temperatures and interactions between soil and vegetation elements in agricultural environments, such as vineyards and orchards. In this study, five existing extrapolation approaches that compute the daily ET from the “instantaneous” remotely sensed sUAS ET estimates and the eddy covariance (EC) flux tower measurements were evaluated under different weather, grapevine variety, and trellis designs. Per assumption (b), the nighttime ET contribution was ignored. Each extrapolation technique (evaporative fraction (EF), solar radiation (Rs), net radiation-to-solar radiation (Rn/Rs) ratio, Gaussian (GA), and Sine) makes use of clear skies and quasi-sinusoidal diurnal variations of hourly ET and other meteorological parameters. The sUAS ET estimates and EC ET measurements were collected over multiple years and times from different vineyard sites in California as part of the USDA Agricultural Research Service Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Optical and thermal sUAS imagery data at 10 cm and 60 cm, respectively, were collected by the Utah State University AggieAir sUAS Program and used in the Two-Source Energy Balance (TSEB) model to estimate the instantaneous or hourly sUAS ET at overpass time. The hourly ET from the EC measurements was also used to validate the extrapolation techniques. Overall, the analysis using EC measurements indicates that the Rs, EF, and GA approaches presented the best goodness-of-fit statistics for a window of time between 1030 and 1330 PST (Pacific Standard Time), with the Rs approach yielding better agreement with the EC measurements. Similar results were found using TSEB and sUAS data. The 1030–1330 time window also provided the greatest agreement between the actual daily EC ET and the extrapolated TSEB daily ET, with the Rs approach again yielding better agreement with the ground measurements. The expected accuracy of the upscaled TSEB daily ET estimates across all vineyard sites in California is below 0.5 mm/day, (EC extrapolation accuracy was found to be 0.34 mm/day), making the daily scale results from TSEB reliable and suitable for day-to-day water management applications.

Comparison of evapotranspiration methods in the DSSAT Cropping System Model: I. Global sensitivity analysis

Global sensitivity analysis (GSA) is useful for evaluating the responsiveness of agroecosystem models to input parameter adjustments. Evaluations of model sensitivity for diverse water status conditions and evapotranspiration (ET) algorithms will facilitate better use of models to provide water management recommendations. The objective of this study was to conduct a GSA to identify influential parameters in the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM), specifically using the CROPGRO-Cotton module with data from cotton field studies conducted in 2000, 2001, and 2008 at Bushland, Texas. The field studies tested fully-irrigated, deficit-irrigated, and dryland cotton production in a semi-arid environment. Using high performance computing resources, a GSA was conducted to evaluate the sensitivity of 24 model outputs with respect to 37 model input parameters. The GSA was conducted for six different ET methodologies available in the model. With first-order sensitivity indices <0.05, nearly half of the tested input parameters did not influence any model output for any of the tested simulation scenarios. Among the parameters with first-order sensitivity indices >0.05, eleven were cultivar parameters that controlled crop development and growth, and five were soil parameters that specified initial soil water conditions, soil water limits, drainage rate, and root growth characteristics. The influences of another soil parameter and one ET parameter were relevant only for the ET methods that required them. Large differences in sensitivity indices were found based on the choice between two soil water evaporation methods. In addition to providing insights for other applications of this model, the results specifically informed further efforts to evaluate the model using measured data from the Bushland cotton studies to compare performance among the six ET methods, as reported in a companion paper.

Numerical Approaches for Estimating Daily River Leakage from Arid Ephemeral Streams

Despite the significance of river leakage to riparian ecosystems in arid/semi-arid regions, a true understanding and the accurate quantification of the leakage processes of ephemeral rivers in these regions remain elusive. In this study, the patterns of river infiltration and the associated controlling factors in an approximately 150-km section of the Donghe River (lower Heihe River, China) were revealed using a combination of field investigations and modelling techniques. The results showed that from 21 April 2010 to 7 September 2012, river water leakage accounted for 33% of the total river runoff in the simulated segments. A sensitivity analysis showed that the simulated infiltration rates were most sensitive to the aquifer hydraulic conductivity and the maximum evapotranspiration (ET) rate. However, the river leakage rate, i.e., the ratio of the leakage volume to the total runoff volume, of a single runoff event relies heavily on the total runoff volume and river flow rate. In addition to the hydraulic parameters of riverbeds, the characteristics of ET parameters are equally important for quantifying the flux exchange between arid ephemeral streams and underlying aquifers. Coupled surface/groundwater models, which aim to estimate river leakage, should consider riparian zones because these areas play a dominant role in the formation of leakage from the river for recharging via ET. The results of this paper can be used as a reference for water resource planning and management in regulated river basins to help maintain riparian ecosystems in arid regions.

Runoff Predicting and Variation Analysis in Upper Ganjiang Basin under Projected Climate Changes

Catchment runoff is significantly affected by climate condition changes. Predicting the runoff and analyzing its variations under future climates play a vital role in water security, water resource management, and the sustainable development of the catchment. In traditional hydrological modeling, fixed model parameters are usually used to transfer the global climate models (GCMs) to runoff, while the hydrologic model parameters may be time-varying. It is more appropriate to use the time-variant parameter for runoff modeling. This is achieved by incorporating the time-variant parameter approach into a two-parameter water balance model (TWBM) through the construction of time-variant parameter functions based on the identified catchment climate indicators. Using the Ganjiang Basin with an outlet of the Dongbei Hydrological Station as the study area, we developed time-variant parameter scenarios of the TWBM model and selected the best-performed parameter functions to predict future runoff and analyze its variations under the climate model projection of the BCC-CSM1.1(m). To synthetically assess the model performance improvements using the time-variant parameter approach, an index Δ was developed by combining the Nash–Sutcliffe efficiency, the volume error, the Box–Cox transformed root-mean-square error, and the Kling–Gupta efficiency with equivalent weight. The results show that the TWBM model with time-variant C (evapotranspiration parameter) and SC (water storage capacity of catchment), where growing and non-growing seasons are considered for C, outperformed the model with constant parameters with a Δ value of approximately 5% and 10% for the calibration and validation periods, respectively. The mean annual values of runoff predictions under the four representative concentration pathways (RCPs) exhibited a decreasing trend over the future three decades (2021–2050) when compared to the runoff simulations in the baseline period (1982–2011), where the values were about −9.9%, −19.5%, −16.6%, and −11.4% for the RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The decreasing trend of future precipitation exerts impacts on runoff decline. Generally, the mean monthly changes of runoff predictions showed a decreasing trend from January to August for almost all of the RCPs, while an increasing trend existed from September to November, along with fluctuations among different RCPs. This study can provide beneficial references to comprehensively understand the impacts of climate change on runoff prediction and thus improve the regional strategy for future water resource management.

Physically Based Estimation of Rainfall Thresholds Triggering Shallow Landslides in Volcanic Slopes of Southern Italy

On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.

Estimation of evapotranspiration and its parameters for pine, switchgrass, and intercropping with remotely-sensed images based geospatial modeling

Intercropping switchgrass (Panicum virgatum) with pine can increase bioenergy feedstock production without land opportunity costs but can potentially alter water budgets. Measuring evapotranspiration (ET) and its parameters (stomatal conductance (gs), leaf area index (LAI), canopy temperature (Tc), and soil moisture (SM)) across cropping systems is costly and time-consuming. However, interpretation of remotely-sensed data can facilitate the effective assessment of relative ET demands among competing forest landuses. This study develops and tests geospatial models informed by a normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), vegetation vigor index (VVI), and other spectral information to estimate ET and its parameters, which are measured on experimental watersheds with young pines and natural understory (YP), switchgrass only (SG), and young pine intercropped with switchgrass (IC). The treatment watersheds were replicated on three sites located across the Southeastern U.S. in Carteret, NC; Calhoun, MS; and Greene, AL. Despite the growth inconsistency for the SG only treatment, remote modeling estimation of ET parameters yielded an acceptable R2 > 0.70, and the ET model yielded R2 of 0.50 and a standard error of prediction of 0.94. However, ET and ET parameter model estimation for the IC performed somewhat less satisfactorily, with an R2 of 0.47, 0.59, 0.56, 0.81, and 0.57 for ET, LAI, gs, Tc, and SM, respectively, potentially due to inconsistencies in Landsat image pixel size and landuse homogeneity. Moreover, ET parameter models for the YP site performed rather poorly, with R2 = 0.28, 0.63, and 0.76 for LAI, gs, and Tc, respectively. Additionally, image analysis automation was created with Python scripting and geospatial models. The findings from this study suggest that inclusion of more spatial variability, sound data mining, ultra-high resolution imagery and advanced image processing approaches to account for potential modeling uncertainties can enhance the predictive capability of models to remotely estimate environmental parameters including ET. Radial Basis Function Network (RBFN) based models provided promising results for estimating ET and ET parameters using remotely-sensed digital information when they are prepared with advanced data mining, but it is likely that laypersons may find these models difficult to use. However, forest managers with access to neural network software can use our devised RBFN training models for estimating those forest hydrologic parameters with better accuracy.

A Long–Term Response-Based Rainfall-Runoff Hydrologic Model: Case Study of The Upper Blue Nile

This study develops a response-based hydrologic model for long-term (continuous) rainfall-runoff simulations over the catchment areas of big rivers. The model overcomes the typical difficulties in estimating infiltration and evapotranspiration parameters using a modified version of the Soil Conservation Service curve number SCS-CN method. In addition, the model simulates the surface and groundwater hydrograph components using the response unit-hydrograph approach instead of using a linear reservoir routing approach for routing surface and groundwater to the basin outlet. The unit-responses are Geographic Information Systems (GIS)-pre-calculated on a semi-distributed short-term basis and applied in the simulation in every time step. The unit responses are based on the time-area technique that can better simulate the real routing behavior of the basin. The model is less sensitive to groundwater infiltration parameters since groundwater is actually controlled by the surface component and not the opposite. For that reason, the model is called the SCHydro model (Surface Controlled Hydrologic model). The model is tested on the upper Blue Nile catchment area using 28 years daily river flow data set for calibration and validation. The results show that SCHydro model can simulate the long-term transforming behavior of the upper Blue Nile basin. Our initial assessment of the model indicates that the model is a promising tool for long-term river flow simulations, especially for long-term forecasting purposes due to its stability in performing the water balance.

Estimating evapotranspiration parameters by inverse modelling and non-linear optimization

The use of models like HYDRUS in planning irrigation and fertigation scheduling is increasingly researched. Simulation of the root zone processes using HYDRUS largely depends on characterizing parameters related to unsaturated hydraulic conductivity, root growth and water uptake dynamics. A methodology for estimating evapotranspiration parameters for drip irrigated paddy is developed in the present work. The methodology involves soil moisture logging of root zone followed by modelling the dynamics of soil water movement in the root zone by inversely solving the Richards’ equation and evapotranspiration parameters estimation by non-linear programming. All the computer programming was done with MS-EXCEL and it is found that this tool is versatile for this purpose. The results of this work are very useful for using HYDRUS in developing optimal irrigation and fertigation schedule. A threshold level of soil water suction pressure for irrigation scheduling of paddy was also obtained through this work. Temporal changes in the location of the average volumetric water content and average evapotranspiration in the root zone were evaluated. These data are useful for developing guidelines for soil water sensor placement in automatic irrigation triggers.

Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

AbstractAccurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ETp) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ETp method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

Modelling time-variant parameters of a two-parameter monthly water balance model

Parameters are usually assumed to be stationary, and regarded as constants in hydrological modelling. However, studies have shown that model parameters may vary temporally due to human activities, and climate variability and changes. This study proposes a framework for quantifying hydrological model parameters as functions of time-variant catchment properties, aiming to improve the capability of capturing hydrograph and the extrapolative ability of hydrological models under a changing environment. The framework includes four steps: (1) estimating model parameters by using an ensemble Kalman filter based on the observations; (2) analyzing correlations between estimated parameter values and catchment properties; (3) constructing a set of parameter functions based on the identified catchment properties and the proposed functional forms; and (4) selecting and testing the best-performed model. As a demonstration of the framework, the monthly water balance for Tongtianhe and Ganjiang basins in China with different climate are simulated using a two-parameter monthly water balance model. Results from the Tongtianhe Basin show that considering the time-variant evapotranspiration parameter (C) brings improvement in low flows when water storage capacity (SC) is treated as constant since there is no significant improvement in runoff simulation when SC is treated as a time-variant parameter. The application to Ganjiang Basin shows that reasonable improvements are achieved when both C and SC are treated as time-variant, especially in low and high flows. The presented framework provides a useful tool for estimating time-variant parameters of hydrological models, thereby leading to more reliable model predictions under a changing environment.

Simulation of maize evapotranspiration: An inter-comparison among 29 maize models

Crop yield can be affected by crop water use and vice versa, so when trying to simulate one or the other, it can be important that both are simulated well. In a prior inter-comparison among maize growth models, evapotranspiration (ET) predictions varied widely, but no observations of actual ET were available for comparison. Therefore, this follow-up study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Observations of daily ET using the eddy covariance technique from an 8-year-long (2006–2013) experiment conducted at Ames, IA were used as the standard for comparison among models. Simulation results from 29 models are reported herein. In the first “blind” phase for which only weather, soils, phenology, and management information were provided to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. Subsequent three phases provided (1) leaf area indices for all years, (2) all daily ET and agronomic data for a typical year (2011), and (3) all data for all years, thus allowing the modelers to progressively calibrate their models as more information was provided, but the range among ET estimates still varied by a factor of two or more. Much of the variability among the models was due to differing estimates of potential evapotranspiration, which suggests an avenue for substantial model improvement. Nevertheless, the ensemble median values were generally close to the observations, and the medians were best (had the lowest mean squared deviations from observations, MSD) for several ET categories for inter-comparison, but not all. Further, the medians were best when considering both ET and agronomic parameters together. The best six models with the lowest MSDs were identified for several ET and agronomic categories, and they proved to vary widely in complexity in spite of having similar prediction accuracies. At the same time, other models with apparently similar approaches were not as accurate. The models that are widely used tended to perform better, leading us speculate that a larger number of users testing these models over a wider range of conditions likely has led to improvement. User experience and skill at calibration and dealing with missing input data likely were also a factor in determining the accuracy of model predictions. In several cases different versions of a model within the same family of models were run, and these within-family inter-comparisons identified particular approaches that were better while other factors were held constant. Thus, improvement is needed in many of the models with regard to their ability to simulate ET over a wide range of conditions, and several aspects for progress have been identified, especially in their simulation of potential ET.

Improving Alpine Summertime Streamflow Simulations by the Incorporation of Evapotranspiration Data

Over the last decade, autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin’s outlet. In alpine settings, spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was auto-calibrated with the SUFI-2 routine. A mountainous watershed from Idaho was examined (Upper North Fork). In this study, this basin was calibrated using three estimates of evapotranspiration (ET): Moderate Resolution Imagining Spectrometer (MODIS), Simplified Surface Energy Balance, and Global Land Evaporation: the Amsterdam Model. The MODIS product in particular, had the greatest utility in helping to constrain SWAT parameters that have a high sensitivity to ET. Streamflow simulations that utilize these ET parameter values have improved recessional and summertime streamflow performances during calibration (2007 to 2011) and validation (2012 to 2014) periods. Streamflow performance was monitored with standard objective metrics (Bias and Nash Sutcliffe coefficients) that quantified overall, recessional, and summertime peak flows. This approach yielded dramatic enhancements for all three observations. These results demonstrate the utility of this approach for improving watershed modeling fidelity outside the main snowmelt season.

Spectral Mixture Analysis as a Unified Framework for the Remote Sensing of Evapotranspiration

This study illustrates a unified, physically-based framework for mapping landscape parameters of evapotranspiration (ET) using spectral mixture analysis (SMA). The framework integrates two widely used approaches by relating radiometric surface temperature to subpixel fractions of substrate (S), vegetation (V), and dark (D) spectral endmembers (EMs). Spatial and temporal variations in these spectral endmember fractions reflect process-driven variations in soil moisture, vegetation phenology, and illumination. Using all available Landsat 8 scenes from the peak growing season in the agriculturally diverse Sacramento Valley of northern California, we characterize the spatiotemporal relationships between each of the S, V, D land cover fractions and apparent brightness temperature (T) using bivariate distributions in the ET parameter spaces. The dark fraction scales inversely with shortwave broadband albedo (ρ &lt; −0.98), and show a multilinear relationship to T. Substrate fraction estimates show a consistent (ρ ≈ 0.7 to 0.9) linear relationship to T. The vegetation fraction showed the expected triangular relationship to T. However, the bivariate distribution of V and T shows more distinct clustering than the distributions of Normalized Difference Vegetation Index (NDVI)-based proxies and T. Following the Triangle Method, the V fraction is used with T to compute the spatial maps of the ET fraction (EF; the ratio of the actual total ET to the net radiation) and moisture availability (Mo; the ratio of the actual soil surface evaporation to potential ET at the soil surface). EF and Mo estimates derived from the V fraction distinguish among rice growth stages, and between rice and non-rice agriculture, more clearly than those derived from transformed NDVI proxies. Met station-based reference ET &amp; soil temperatures also track vegetation fraction-based estimates of EF &amp; Mo more closely than do NDVI-based estimates of EF &amp; Mo. The proposed approach using S, V, D land cover fractions in conjunction with T (SVD+T) provides a physically-based conceptual framework that unifies two widely-used approaches by simultaneously mapping the effects of albedo and vegetation abundance on the surface temperature field. The additional information provided by the third (Substrate) fraction suggests a potential avenue for ET model improvement by providing an explicit observational constraint on the exposed soil fraction and its moisture-modulated brightness. The structures of the T, EF &amp; Mo vs SVD feature spaces are complementary and that can be interpreted in the context of physical variables that scale linearly and that can be represented directly in process models. Using the structure of the feature spaces to represent the spatiotemporal trajectory of crop phenology is possible in agricultural settings, because variations in the timing of planting and irrigation result in continuous trajectories in the physical parameter spaces that are represented by the feature spaces. The linear scaling properties of the SMA fraction estimates from meter to kilometer scales also facilitate the vicarious validation of ET estimates using multiple resolutions of imagery.

Evaluating evapotranspiration estimation methods in APEX model for dryland cropping systems in a semi-arid region

Evapotranspiration (ET), is a major component of the hydrologic budget and therefore it requires accurate estimation. The Agricultural Policy/Environmental eXtender (APEX), a hydrologic and water quality model developed for evaluating the effect of agricultural production management practices on the environment. It has five different methods to simulate ET. The objectives of this study were to: determine the impact of using different ET methods in APEX on sensitive ET parameters in semi-arid environments, determine reasonable range of values for sensitive parameters, and compare performance of these methods using multiple criteria. ET and crop yield data measured in the Lysimeter fields located in the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas were used to calibrate and validate the model. Results indicated that selection of statistical model performance measure and ET method affects the number of sensitive parameters and parameter rank. The number of sensitive parameters remained relatively stable among ET simulation methods but there was large variability in parameter sensitivity ranks. It is also important that users carefully choose appropriate statistical measure to use depending on the goals of their study. With the exception of maximum rainfall intercept, exponent coefficient rainfall, SCS index coefficient, rain intercept coefficient, and root growth soil strength, all methods had similar ranges of values for the sensitive parameters. In general there were no large differences in the performance of ET methods. However, Penman-Monteith method simulated ET relatively better than the other methods, which may be explained by the fact that it is a physically-based method with many weather variables whose data was available for the study area. However, the study findings indicate that the other ET methods can provide satisfactory results in regions with limited weather data.