ORCID Profile
0000-0002-6231-0085
Current Organisations
Amherst College
,
National Center for Atmospheric Research
,
Colorado School of Mines
,
University of Washington
,
University of St Andrews
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Publisher: Copernicus GmbH
Date: 11-07-2017
DOI: 10.5194/HESS-21-3427-2017
Abstract: Abstract. The ersity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide ex les of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our ersity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.
Publisher: Copernicus GmbH
Date: 18-12-2018
Abstract: Abstract. Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union (EGU) in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals.
Publisher: American Meteorological Society
Date: 10-2013
Abstract: Assessing climate change risk to municipal water supplies is often conducted by hydrologic modeling specific to local watersheds and infrastructure to ensure that outputs are compatible with existing planning frameworks and processes. This study leverages the modeling capacity of an operational National Weather Service River Forecast Center to explore the potential impacts of future climate-driven hydrologic changes on factors important to planning at the Salt Lake City Department of Public Utilities (SLC). Hydrologic modeling results for the study area align with prior research in showing that temperature changes alone will lead to earlier runoff and reduced runoff volume. The sensitivity of average annual flow to temperature varies significantly between watersheds, averaging −3.8% °F−1 and ranging from −1.8% to −6.5% flow reduction per degree Fahrenheit of warming. The largest flow reductions occur during the high water demand months of May–September. Precipitation drives hydrologic response more strongly than temperature, with each 1% precipitation change producing an average 1.9% runoff change of the same sign. This paper explores the consequences of climate change for the reliability of SLC's water supply system using scenarios that include hydrologic changes in average conditions, severe drought scenarios, and future water demand test cases. The most significant water management impacts will be earlier and reduced runoff volume, which threaten the system's ability to maintain adequate streamflow and storage to meet late-summer water demands.
Publisher: American Meteorological Society
Date: 05-2017
Abstract: GCMs are used by many national weather services to produce seasonal outlooks of atmospheric and oceanic conditions and fluxes. Postprocessing is often a necessary step before GCM forecasts can be applied in practice. Quantile mapping (QM) is rapidly becoming the method of choice by operational agencies to postprocess raw GCM outputs. The authors investigate whether QM is appropriate for this task. Ensemble forecast postprocessing methods should aim to 1) correct bias, 2) ensure forecasts are reliable in ensemble spread, and 3) guarantee forecasts are at least as skillful as climatology, a property called “coherence.” This study evaluates the effectiveness of QM in achieving these aims by applying it to precipitation forecasts from the POAMA model. It is shown that while QM is highly effective in correcting bias, it cannot ensure reliability in forecast ensemble spread or guarantee coherence. This is because QM ignores the correlation between raw ensemble forecasts and observations. When raw forecasts are not significantly positively correlated with observations, QM tends to produce negatively skillful forecasts. Even when there is significant positive correlation, QM cannot ensure reliability and coherence for postprocessed forecasts. Therefore, QM is not a fully satisfactory method for postprocessing forecasts where the issues of bias, reliability, and coherence pre-exist. Alternative postprocessing methods based on ensemble model output statistics (EMOS) are available that achieve not only unbiased but also reliable and coherent forecasts. This is shown with one such alternative, the Bayesian joint probability modeling approach.
Publisher: American Meteorological Society
Date: 06-2016
Abstract: Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E0, as in sustained droughts, and 2) parallel ET and E0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E0, a long-term, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in Part II.
Publisher: American Geophysical Union (AGU)
Date: 03-2011
DOI: 10.1029/2010WR010101
Publisher: American Meteorological Society
Date: 10-2013
Abstract: A hydrometric network design approach is developed for enhancing statistical seasonal streamflow forecasts. The approach employs gridded, model-simulated water balance variables as predictors in equations generated via principal components regression in order to identify locations for additional observations that most improve forecast skill. The approach is applied toward the expansion of the Natural Resources Conservation Service (NRCS) Snowpack Telemetry (SNOTEL) network in 24 western U.S. basins using two forecasting scenarios: one that assumes the currently standard predictors of snow water equivalent and water year-to-date precipitation and one that considers soil moisture as an additional predictor variable. Resulting improvements are spatially and temporally analyzed, attributed to dominant predictor contributions, and evaluated in the context of operational NRCS forecasts, ensemble-based National Weather Service (NWS) forecasts, and historical as-issued NRCS/NWS coordinated forecasts. Findings indicate that, except for basins with sparse existing networks, substantial improvements in forecast skill are only possible through the addition of soil moisture variables. Furthermore, locations identified as optimal for soil moisture sensor installation are primarily found in regions of low to mid elevation, in contrast to the higher elevations where SNOTEL stations are traditionally situated. The study corroborates prior research while demonstrating that soil moisture data can explicitly improve operational water supply forecasts (particularly during the accumulation season), that statistical forecasts are comparable in skill to ensemble-based forecasts, and that simulated hydrologic data can be combined with observations to improve statistical forecasts. The approach can be generalized to other settings and applications involving the use of point observations for statistical prediction models.
Publisher: American Meteorological Society
Date: 06-2016
Abstract: Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought however, other climatic factors such as solar radiation, wind speed, and humidity can be important drivers in the depletion of soil moisture and evolution and persistence of drought. This work assesses the Evaporative Demand Drought Index (EDDI) at multiple time scales for several hydroclimates as the second part of a two-part study. EDDI and in idual evaporative demand components were examined as they relate to the dynamic evolution of flash drought over the central United States, characterization of hydrologic drought over the western United States, and comparison to commonly used drought metrics of the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and the evaporative stress index (ESI). Two main advantages of EDDI over other drought indices are that it is independent of precipitation (similar to ESI) and it can be decomposed to identify the role in idual evaporative drivers have on drought onset and persistence. At short time scales, spatial distributions and time series results illustrate that EDDI often indicates drought onset well in advance of the USDM, SPI, and SSI. Results illustrate the benefits of physically based evaporative demand estimates and demonstrate EDDI’s utility and effectiveness in an easy-to-implement agricultural early warning and long-term hydrologic drought–monitoring tool with potential applications in seasonal forecasting and fire-weather monitoring.
Publisher: American Meteorological Society
Date: 08-2012
Abstract: To understand the sources of temporal and spatial variability of atmospheric evaporative demand across the conterminous United States (CONUS), a mean-value, second-moment uncertainty analysis is applied to a spatially distributed dataset of daily synthetic pan evaporation for 1980–2009. This evaporative demand measure is from the “PenPan” model, which is a combination equation calibrated to mimic observations from U.S. class-A evaporation pans and here driven by six North American Land Data Assimilation System variables: temperature, specific humidity, station pressure, wind speed, and downwelling shortwave and longwave radiation. The variability of evaporative demand is decomposed across various time scales into contributions from these drivers. Contrary to popular expectation and much hydrologic practice, temperature is not always the most significant driver of temporal variability in evaporative demand, particularly at subannual time scales. Instead, depending on the season, one of four drivers (temperature, specific humidity, downwelling shortwave radiation, and wind speed) dominates across different regions of CONUS. Temperature generally dominates in the northern continental interior. This analysis assists land surface modelers in balancing parameter parsimony and physical representativeness. Patterns of dominant drivers are shown to cycle seasonally, with clear implications for modeling evaporative demand in operational hydrology or as a metric of climate change and variability. Depending on the region and season, temperature, specific humidity, downwelling shortwave radiation, and wind speed must together be examined, with downwelling longwave radiation as a secondary input. If any variable may be ignored, it is atmospheric pressure. Parameterizations of evaporative demand based solely on temperature should be avoided at all time scales.
Publisher: Copernicus GmbH
Date: 16-01-2017
Abstract: Abstract. The ersity in hydrologic models has historically led to great controversy on the “correct” approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper we revisit key modeling challenges, outlined by Freeze and Harlan nearly 50 years ago, on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our ersity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.
Publisher: American Geophysical Union (AGU)
Date: 04-2015
DOI: 10.1002/2015WR017200
Publisher: Springer Science and Business Media LLC
Date: 03-2020
Publisher: American Geophysical Union (AGU)
Date: 06-2020
DOI: 10.1029/2018WR024053
Publisher: Copernicus GmbH
Date: 05-11-2018
DOI: 10.5194/HESS-22-5735-2018
Abstract: Abstract. Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union (EGU) in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals.
Publisher: American Geophysical Union (AGU)
Date: 04-2015
DOI: 10.1002/2015WR017198
Location: United States of America
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Andrew Wood.