Understanding the present water budget in Himalayan Basins is a challenge due to poor in situ coverage, incomplete or unreliable records, and the limitations of coarse resolution gridded data set. In ...the study, a two‐way coupled implementation of the Weather Research and Forecasting (WRF) Model and the WRF‐Hydro hydrological modeling extension package (WRF/WRF‐Hydro) was employed in its offline configuration, over a 10 year simulation period for a mountainous river basin in North India. A triple nest is employed, in which the innermost domain had 3 km for atmospheric model grids and 300 m for hydrological components. Two microphysical parameterization (MP) schemes are quantitatively evaluated to reveal how differently MP influences orographic‐related precipitation and how it impacts hydrological responses.
The WRF‐Hydro modeling system shows reasonable skill in capturing the spatial and temporal structure of high‐resolution precipitation, and the resulting stream flow hydrographs exhibit a good correspondence with observation at monthly timescales, although the model tends to generally underestimate streamflow amounts. The Thompson Scheme fits better to the observations in the study. More importantly, WRF shows that for high‐altitude precipitation, a high “bias” is exhibited in winter precipitation from WRF, which is about double to triple that as estimated from valley‐sited rain gauges and remotely sensed precipitation estimates from Tropical Rainfall Measuring Mission and Asian Precipitation ‐ Highly‐Resolved Observational Data Integration Towards Evaluation. Given the full annual cycle pattern and amount in high‐altitude precipitation and the statistical correspondence in discharge, it is concluded that the WRF‐Hydro modeling system shows potential for explicitly predicting potential changes in the atmospheric‐hydrology cycle of ungauged or poorly gauged basins.
Plain Language Summary
Understanding the present water budget in Himalayan Basins is a challenge due to poor in situ coverage, incomplete or unreliable records, and the limitations of coarse resolution gridded data set. In a Himalayan headwater river basin, the Weather Research and Forecasting (WRF)‐Hydro modeling system shows reasonable skill in capturing the precipitation and the resulting stream flow hydrographs exhibit a good correspondence with observation at monthly timescales. More importantly, WRF shows that for high‐altitude precipitation, a high “bias” is exhibited in winter precipitation from WRF, which is about double to triple that as estimated from valley‐sited rain gauges and remotely sensed precipitation estimates from both Tropical Rainfall Measuring Mission and Asian Precipitation ‐ Highly‐Resolved Observational Data Integration Towards Evaluation. Given the full annual cycle pattern and amount in high‐altitude precipitation and the statistical correspondence in discharge, it is concluded that the WRF‐Hydro modeling system shows potential for explicitly predicting potential changes in the atmospheric‐hydrology cycle of ungauged or poorly gauged basins.
Key Points
A significant disagreement in high‐altitude precipitation estimates is found between gauge observations, TRMM, APHRODITE, and the WRF
A large amount of precipitation in high mountainous areas in Beas Basin is occurring and is not properly accounted for in TRMM or APHRODITE
WRF‐Hydro modeling system shows skill in capturing monthly discharge variability and the daily discharge distribution
Biogenic volatile organic compound (BVOC) emissions come from a variety of sources, including living above-ground foliar biomass and microbial decomposition of dead organic matter at the soil surface ...(litter and soil organic matter). There are, however, few reports that quantify the contributions of each component. Measurements of emission fluxes are now made above the vegetation canopy, but these include contributions from all sources. BVOC emission models currently include detailed parameterization of the emissions from foliar biomass but do not have an equally descriptive treatment of emissions from litter or other sources. We present here results of laboratory and field experiments to characterize the major parameters that control emissions from litter.
Litter emissions are exponentially dependent on temperature. The moisture content of the litter plays a minor role, except during and immediately following rain events. The percentage of carbon readily available for microbial and other decomposition processes decreases with litter age. These 3 variables are combined in a model to explain over 50% of the variance of individual BVOC emission fluxes measured. The modeled results of litter emissions were compared with above-canopy fluxes. Litter emissions constituted less than 1% of above-canopy emissions for all BVOCs measured. A comparison of terpene oil pools in litter and live needles with above-canopy fluxes suggests that there may be another canopy terpene source in addition to needle storage or that some terpene emissions may be light-dependent.
Ground enclosure measurements indicated that compensation point concentrations of BVOCs (equilibrium between BVOC emission and deposition) were usually higher than ambient air concentrations at the temperature of the measurements.
► Litter BVOC fluxes were measured by gradient flux and enclosure techniques. ► Emissions were shown to have exponential dependence on temperature and moisture. ► A litter BVOC emissions model was developed which successfully reproduced the emission measurements. ► Litter BVOC emissions make only a small contribution to the whole ecosystem flux of the BVOCs measured.
The science of mountainous hydrology spans the atmosphere through the bedrock and inherently crosses physical and disciplinary boundaries: land-atmosphere interactions in complex terrain enhance ...clouds and precipitation, while watersheds retain and release water over a large range of spatial and temporal scales. Limited observations in complex terrain challenge efforts to improve predictive models of the hydrology in the face of rapid changes. The Upper Colorado River exemplifies these challenges, especially with ongoing mismatches between precipitation, snowpack, and discharge. Consequently, the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility has deployed an observatory to the East River Watershed near Crested Butte, Colorado between September 2021 and June 2023 to measure the main atmospheric drivers of water resources, including precipitation, clouds, winds, aerosols, radiation, temperature and humidity. This effort, called the Surface Atmosphere Integrated Field Laboratory (SAIL), is also working in tandem with DOE-sponsored surface and subsurface hydrologists and other federal, state, and local partners. SAIL data can be benchmarks for model development by producing a wide range of observational information on precipitation and its associated processes, including those processes that impact snowpack sublimation and redistribution, aerosol direct radiative effects in the atmosphere and in the snowpack, aerosol impacts on clouds and precipitation, and processes controlling surface fluxes of energy and mass. Preliminary data from SAIL’s first year showcase the rich information content in SAIL’s many data-streams and support testing hypotheses that will ultimately improve scientific understanding and predictability of Upper Colorado River hydrology in 2023 and beyond.
An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season ...precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge.
Abstract
Hillslope‐scale rainfall‐runoff processes leading to a fast catchment response are not explicitly included in land surface models (LSMs) for use in earth system models (ESMs) due to ...computational constraints. This study presents a hybrid‐3D hillslope hydrological model (h3D) that couples a 1‐D vertical soil column model with a lateral pseudo‐2D saturated zone and overland flow model for use in ESMs. By representing vertical and lateral responses separately at different spatial resolutions, h3D is computationally efficient. The h3D model was first tested for three different hillslope planforms (uniform, convergent and divergent). We then compared h3D (with single and multiple soil columns) with a complex physically based 3‐D model and a simple 1‐D soil moisture model coupled with an unconfined aquifer (as typically used in LSMs). It is found that simulations obtained by the simple 1‐D model vary considerably from the complex 3‐D model and are not able to represent hillslope‐scale variations in the lateral flow response. In contrast, the single soil column h3D model shows a much better performance and saves computational time by 2‐3 orders of magnitude compared with the complex 3‐D model. When multiple vertical soil columns are implemented, the resulting hydrological responses (soil moisture, water table depth, and base flow along the hillslope) from h3D are nearly identical to those predicted by the complex 3‐D model, but still saves computational time. As such, the computational efficiency of the h3D model provides a valuable and promising approach to incorporating hillslope‐scale hydrological processes into continental and global‐scale ESMs.
Key Points:
This study presents a hybrid‐3D model for the hillslope hydrological response
Hydrological simulations are similar to those predicted by a 3‐D Richards model
The hybrid‐3D model is computationally 2‐3 orders of magnitude more efficient
Four years of weekly soil water data measured by neutron probe were analyzed to determine average daily, monthly, and seasonal drip-irrigated hybrid poplar water use. The plantation studied is ...located near Boardman, Oregon, on the Columbia River Plateau. Irrigation application data, weekly 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 potential soil water drainage from the lower soil profile. Sites with the potential for significant drainage were removed from the analysis, so that all sites used in the analysis could be assumed to be at steady state. Crop coefficients were calculated using reference evapotranspiration estimates obtained from a nearby AGRIMET weather station. Crop curves were estimated using a fit-by-hand method similar to that outlined by the United Nations Food and Agriculture Organization. Plant water use estimates and crop curves are presented for one-, two- and three-year-old hybrid poplars. Water use estimates represent upper bound estimates relative to the accuracy of the measurements made.
RESERVOIR EVAPORATION IN THE WESTERN UNITED STATES Friedrich, Katja; Grossman, Robert L.; Huntington, Justin ...
Bulletin of the American Meteorological Society,
01/2018, Volume:
99, Issue:
1
Journal Article
Peer reviewed
One way to adapt to and mitigate current and future water scarcity is to manage and store water more efficiently. Reservoirs act as critical buffers to ensure agricultural and municipal water ...deliveries, mitigate flooding, and generate hydroelectric power, yet they often lose significant amounts of water through evaporation, especially in arid and semiarid regions. Despite this fact, reservoir evaporation has been an inconsistently and inaccurately estimated component of the water cycle within the water resource infrastructure of the arid and semiarid western United States. This paper highlights the increasing importance and challenges of correctly estimating and forecasting reservoir evaporation in the current and future climate, as well as the need to bring new ideas and state-of-the-art practices for the estimation of reservoir evaporation into operational use for modern water resource managers. New ideas and practices include i) improving the estimation of reservoir evaporation using up-to-date knowledge, state-of-the-art instrumentation and numerical models, and innovative experimental designs to diagnose processes and accurately forecast evaporation; ii) improving our understanding of spatial and temporal variations in evaporative water loss from existing reservoirs and transferring this knowledge when expanding reservoirs or siting new ones; and iii) implementing an adaptive management plan that incorporates new knowledge, observations, and forecasts of reservoir evaporation to improve water resource management.
Because use of high-resolution hydrologic models is becoming more widespread and estimates are made over large domains, there is a pressing need for systematic evaluation of their performance. Most ...evaluation efforts to date have focused on smaller basins that have been relatively undisturbed by human activity, but there is also a need to benchmark model performance more comprehensively, including basins impacted by human activities. This study benchmarks the long-term performance of two process-oriented, high-resolution, continental-scale hydrologic models that have been developed to assess water availability and risks in the United States (US): the National Water Model v2.1 application of WRF-Hydro (NWMv2.1) and the National Hydrologic Model v1.0 application of the Precipitation–Runoff Modeling System (NHMv1.0). The evaluation is performed on 5390 streamflow gages from 1983 to 2016 (∼ 33 years) at a daily time step, including both natural and human-impacted catchments, representing one of the most comprehensive evaluations over the contiguous US. Using the Kling–Gupta efficiency as the main evaluation metric, the models are compared against a climatological benchmark that accounts for seasonality. Overall, the model applications show similar performance, with better performance in minimally disturbed basins than in those impacted by human activities. Relative regional differences are also similar: the best performance is found in the Northeast, followed by the Southeast, and generally worse performance is found in the Central and West areas. For both models, about 80 % of the sites exceed the seasonal climatological benchmark. Basins that do not exceed the climatological benchmark are further scrutinized to provide model diagnostics for each application. Using the underperforming subset, both models tend to overestimate streamflow volumes in the West, which could be attributed to not accounting for human activities, such as active management. Both models underestimate flow variability, especially the highest flows; this was more pronounced for NHMv1.0. Low flows tended to be overestimated by NWMv2.1, whereas there were both over and underestimations for NHMv1.0, but they were less severe. Although this study focused on model diagnostics for underperforming sites based on the seasonal climatological benchmark, metrics for all sites for both model applications are openly available online.
Robust validation of the space–time structure of remotely sensed precipitation estimates is critical to improving their quality and confident application in water cycle–related research. In this ...work, the performance of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) precipitation product is evaluated against warm season precipitation observations from the North American Monsoon Experiment (NAME) Event Rain Gauge Network (NERN) in the complex terrain region of northwestern Mexico. Analyses of hourly and daily precipitation estimates show that the PERSIANN-CCS captures well active and break periods in the early and mature phases of the monsoon season. While the PERSIANN-CCS generally captures the spatial distribution and timing of diurnal convective rainfall, 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 elevation-dependent biases contribute to a 1–2-h phase shift of the diurnal cycle of precipitation at various elevation bands. For reasons yet to be determined, the PERSIANN-CCS significantly underestimated a few active periods of precipitation during the late or “senescent” phase of the monsoon. Despite these shortcomings, the continuous domain and relatively high spatial resolution of PERSIANN-CCS quantitative precipitation estimates (QPEs) provide useful characterization of precipitation space–time structures in the North American monsoon region of northwestern Mexico, which should prove useful for hydrological applications.
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.
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