Estimated plant water use and crop coefficients for drip-irrigated hybrid polars

Estimations of plant water use can provide great assistance to growers, irrigators, engineers and water resource planners. This is especially true concerning the introduction of a new crop into irrigated agriculture. Growing hybrid poplar trees for wood chip stock and veneer production under agronomic practices is currently being explored as an alternative to traditional forestry practices. To this author's knowledge, no water use estimates or crop coefficients, the ratio of a specified crop evapotranspiration to a reference crop evapotranspiration, have been verified for hybrid poplars grown under drip irrigation. Four years of weekly, neutron probe measured, soil water data were analyzed to determine averaged daily, monthly and seasonal plant water use, or crop evapotranspiration. The plantation studied was located near Boardman, Oregon on the arid Columbia River Plateau of North-Central Oregon. Water was applied by periodic applications via drip irrigation. Irrigation application data, weekly recorded rainfall and changes in soil water content permitted the construction of a soil water balance model to calculate weekly hybrid poplar water use. Drainage was estimated by calculating a potential soil water flux from the lower soil profile. Sites with significant estimated potential drainage were removed from the analysis so that all sites used in the development coefficients were calculated using reference evapotranspiration estimates obtained from a nearby AGRIMET weather station. Mean crop coefficients were estimated using a 2nd order polynomial with 95% confidence intervals. Plant water use estimates and crop curves are presented for one, two and three year old hybrid poplars. Numerical simulation of irrigation practices was attempted using weekly soil water content and soil physical characterization data. Parameter optimization and numerical simulations were attempted using the HYDRUS-2D Soil Water and Solute Transport model. Parameter optimization and numerical simulations were largely unsuccessful due to lack of adequate soil physical and root zone system representation and dimensional differences between drip irrigation processes and the model design used in this study

Enhancing the Structure of the WRF-Hydro Hydrologic Model for Semiarid Environments

In August 2016, the National Weather Service Office of Water Prediction (NWS/OWP) of the National Oceanic and Atmospheric Administration (NOAA) implemented the operational National Water Model (NWM) to simulate and forecast streamflow, soil moisture, and other model states throughout the contiguous United States. Based on the architecture of the WRF-Hydro hydrologic model, the NWM does not currently resolve channel infiltration, an important component of the water balance of the semiarid western United States. Here, we demonstrate the benefit of implementing a conceptual channel infiltration function (from the KINEROS2 semidistributed hydrologic model) into the WRF-Hydro model architecture, configured as NWM v1.1. After calibration, the updated WRF-Hydro model exhibits reduced streamflow errors for the Walnut Gulch Experimental Watershed (WGEW) and the Babocomari River in southeast Arizona. Model calibration was performed using NLDAS-2 atmospheric forcing, available from the NOAA National Centers for Environmental Prediction (NCEP), paired with precipitation forcing from NLDAS-2, NCEP Stage IV, or local gauge precipitation. Including channel infiltration within WRF-Hydro results in a physically realistic hydrologic response in the WGEW, when the model is forced with high-resolution, gauge-based precipitation in lieu of a national product. The value of accounting for channel loss is also demonstrated in the Babocomari basin, where the drainage area is greater and the cumulative effect of channel infiltration is more important. Accounting for channel infiltration loss thus improves the streamflow behavior simulated by the calibrated model and reduces evapotranspiration bias when gauge precipitation is used as forcing. However, calibration also results in increased high soil moisture bias, which is likely due to underlying limitations of the NWM structure and calibration methodology.University Corporation for Atmospheric Science (UCAR) COMET Cooperative Project; NOAA Joint Technology Transfer Initiative (JTTI) Federal Grant [NA17OAR4590183]6 month embargo; published online 22 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A Unified Approach for Process-Based Hydrologic Modeling: 2. Model Implementation and Case Studies

This work advances a unified approach to process-based hydrologic modeling, which we term the “Structure for Unifying Multiple Modeling Alternatives (SUMMA).” The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty

A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies

This work advances a unified approach to process-based hydrologic modeling, which we term the ‘‘Structure for Unifying Multiple Modeling Alternatives (SUMMA).’’ The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty.Keywords: unified model, scaling behavior, hydrometeorologyKeywords: unified model, scaling behavior, hydrometeorolog

Evaluating the hydro-estimator satellite rainfall algorithm over a mountainous region

This study investigates the performance of the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) operational rainfall estimation algorithm, called the hydro-estimator (HE), with and without its orographic correction method, in its depiction of the timing, intensity and duration of convective rainfall in general, and of the topography-rainfall relationship in particular. An event-based rainfall observation network in north-west Mexico, established as part of the North American monsoon experiment (NAME), provides gauge-based precipitation measurements with sufficient temporal and spatial sampling characteristics to examine the climatological structure of diurnal convective activity over north-west Mexico. In this study, rainfall estimates from the HE algorithm were evaluated against point observations collected from 49 rain gauges from August until the end of September in 2002 and from 79 gauges from August to September in 2003. While the HE with orographic correction to some extent captures the spatial distribution and timing of diurnal convective events, elevation-dependent biases exist, which are characterized by an underestimate in the occurrence of light precipitation at high elevations and an overestimate in the occurrence of precipitation at low elevations. The potential of the HE in providing high spatial and temporal resolution data is also evaluated using a hydrological model over the North American monsoon (NAM) region. The findings suggest that continued improvement to the HE orographic correction scheme is warranted in order to advance quantitative precipitation estimation in complex terrain regions and for use in hydrologic applications

A Process-Based, Fully Distributed Soil Erosion and Sediment Transport Model for WRF-Hydro

A soil erosion and sediment transport model (WRF-Hydro-Sed) is introduced to WRF-Hydro. As a process-based, fully distributed soil erosion model, WRF-Hydro-Sed accounts for both overland and channel processes. Model performance is evaluated using observed rain gauge, streamflow, and sediment concentration data during rainfall events in the Goodwin Creek Experimental Watershed in Mississippi, USA. Both streamflow and sediment yield can be calibrated and validated successfully at a watershed scale during rainfall events. Further discussion reveals the model’s uncertainty and the applicability of calibrated hydro- and sediment parameters to different events. While an intensive calibration over multiple events can improve the model’s performance to a certain degree compared with single event-based calibration, it might not be an optimal strategy to carry out considering the tremendous computational resources needed