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 meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

Abstract. A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology-hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance. The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent. The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices. The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph

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

Modeled sensitivities of the North American Monsoon

The North American Monsoon System (NAMS) is an important climatological feature of much of southwestern North America because it is responsible for large portions of the annual rainfall in many otherwise arid and semi-arid environments. This dissertation explores issues related to numerical simulation of the North American Monsoon climate. Simulation studies using both an atmospheric general circulation model (AGCM) and a regional climate model (RCM), forced by model analyzed boundary conditions, are presented. The RCM was run for a single season with three different convective parameterization schemes for a single season to assess the sensitivity to convective representation. The main conclusion from these simulations was that substantial differences in both the time-integrated thermodynamic and circulation structures of the simulated July 1999 NAM atmosphere evolve in the simulations when different convective parameterization schemes (CPSs) are used. All simulations reproduced the maximum of precipitation along the western slope of the Sierra Madre Occidental. However, root mean squared errors and model biases in precipitation and surface climate variables were substantial, and showed strong regional dependencies between each of the simulations. There are large differences in the modeled monthly-total surface runoff between simulations. These differences appear to be more closely related to differences in local, precipitation intensity than to time-average or basin-average intensity. It was found that many features of the North American Monsoon were poorly simulated by the AGCM used in its current configuration when using a yearly repeating cycle of sea-surface temperatures. In particular, the model is unable to simulate the regional patterns of monsoon circulation and rainfall. Modeled rainfall over the southwest U.S. and Mexico is much too low, while tropical precipitation is overestimated. Anomalous sea-surface temperature forcing in the Pacific Ocean also induced model responses that resemble observed responses suggesting that sea-surface temperatures may play a modest role in establishing the monsoon circulation and hence in the generation of monsoon rainfall

Comparing one-way and two-way coupled hydrometeorological forecasting systems for flood forecasting in the mediterranean region

A pair of hydro-meteorological modeling systems were calibrated and evaluated for the Ayalon basin in central Israel to assess the advantages and limitations of one-way versus two-way coupled modeling systems for flood prediction. The models used included the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) model and the Weather Research and Forecasting (WRF) Hydro modeling system. The models were forced by observed, interpolated precipitation from rain-gauges within the basin, and with modeled precipitation from the WRF atmospheric model. Detailed calibration and evaluation was carried out for two major winter storms in January and December 2013. Then, both modeling systems were executed and evaluated in an operational mode for the full 2014/2015 rainy season. Outputs from these simulations were compared to observed measurements from the hydrometric station at the Ayalon basin outlet. Various statistical metrics were employed to quantify and analyze the results: correlation, Root Mean Square Error (RMSE) and the Nash–Sutcliffe (NS) efficiency coefficient. Foremost, the results presented in this study highlight the sensitivity of hydrological responses to different sources of simulated and observed precipitation data, and demonstrate improvement, although not significant, at the Hydrological response, like simulated hydrographs. With observed precipitation data both calibrated models closely simulated the observed hydrographs. The two-way coupled WRF/WRF-Hydro modeling system produced improved both the precipitation and hydrological simulations as compared to the one-way WRF simulations. Findings from this study, as well as previous studies, suggest that the use of two-way atmospheric-hydrological coupling has the potential to improve precipitation and, therefore, hydrological forecasts for early flood warning applications. However, more research needed in order to better understand the land-atmosphere coupling mechanisms driving hydrometeorological processes on a wider variety precipitation and terrestrial hydrologic systems