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

Influence of initial soil moisture and vegetation conditions on monsoon precipitation events in northwest México

Land surface conditions including soil moisture and vegetation states are expected to play important roles in the development of the daytime boundary layer and the formation of convective precipitation. For areas with an in-phase seasonality of radiation and precipitation, such as the North American Monsoon (NAM) region, diagnosing the direct contributions of each effect is difficult given the co-occurrence of high soil moisture and vegetation greening during the warm season. In this study, we use the WRF-Hydro modeling system to simulate the interactions between the land surface and atmosphere within a large watershed in northwest México subject to the influence of the NAM. After testing the coupled simulations against a bias-corrected reanalysis product for two summer periods in 2004 and 2013, we conduct a series of storm-scale modeling experiments that separately vary the initial soil moisture and vegetation conditions. Results reveal that both soil moisture and vegetation anomalies can positively affect convective precipitation, although their influence on boundary layer development is different. We then diagnose the specific land-atmosphere mechanisms by which the land surface states positively influence convective precipitation. Under high land surface anomalies, such as initial soil moisture equal to field capacity or the maximum vegetation greening state, storm-scale (48 h) precipitation accumulations can be increased up to 26 mm. As a result, improvements in how land surface conditions are initialized either through remote sensing or sensor networks are critical for enhancing precipitation prediction systems in the NAM region

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

Modeling the Hydrologic Influence of Subsurface Tile Drainage Using the National Water Model

Subsurface tile drainage (TD) is a dominant agriculture water management practice in the United States (US) to enhance crop production in poorly drained soils. Assessments of field-level or watershed-level (105 km2) impacts of TD on hydrology. The National Water Model (NWM) is a distributed 1-km resolution hydrological model designed to provide accurate streamflow forecasts at 2.7 million reaches across the US. The current NWM lacks TD representation which adds considerable uncertainty to streamflow forecasts in heavily tile-drained areas. In this study, we quantify the performance of the NWM with a newly incorporated tile-drainage scheme over the heavily tile-drained Midwestern US. Employing a TD scheme enhanced the uncalibrated NWM performance by about 20–50% of the fully calibrated NWM (Calib). The calibrated NWM with tile drainage (CalibTD) showed enhanced accuracy with higher event hit rates and lower false alarm rates than Calib. CalibTD showed better performance in high-flow estimations as TD increased streamflow peaks (14%), volume (2.3%), and baseflow (11%). Regional water balance analysis indicated that TD significantly reduced surface runoff (−7% to −29%), groundwater recharge (−43% to −50%), evapotranspiration (−7% to −13%), and soil moisture content (−2% to −3%). However, TD significantly increased soil profile lateral flow (27.7%) along with infiltration and soil water storage potential. Overall, our findings highlight the importance of incorporating the TD process into the operational configuration of the NWM.This aritcle is published as Valayamkunnath, Prasanth, David J. Gochis, Fei Chen, Michael Barlage, and Kristie J. Franz. "Modeling the hydrologic influence of subsurface tile drainage using the National Water Model." Water Resources Research 58, no. 4 (2022): e2021WR031242. https://doi.org/10.1029/2021WR031242. This article is a U.S. Government work and is in the public domain in the USA