AFFILIATIONS: MCENERY—Water Resource Center, Texas Tech University, Lubbock, Texas; INGRAM—Office of Hydrologic Development, NOAA’s National Weather Service, Silver Spring, Maryland; DUAN— Lawrence Livermore National Laboratory, Livermore, California; ADAMS— Ohio River Forecast Center, NOAA’s National Weather Service, Wilmington, Ohio; ANDERSON—Office of Science and Technology, NOAA’s National ...

In this paper, the influence of four key issues on wavelet-based analysis of hydrologic series’ complexity under multi-temporal scales, including the choice of mother wavelet, noise, estimation of probability density function and trend of series data, was first studied. Then, the complexities of several representative hydrologic series data were quantified and described, based on which the perf...

The Hydrologic Research Laboratory of the National Weather Service Office of Hydrology is developing its next generation of software for the conduct of the National Weather Service Hydrologic Services Program. The Integrated Hydrologic Forecast System (IHFS) project is currently focused on developing and prototyping software and data architecture components of the system. The prototype involves...

Both local and large-scale processes affect the Amazon hydrologic cycle. We investigate the impact of deep soils on the atmosphere through local feedbacks. The Simple Biosphere model, version 3 (SiB3), is coupled to a single column model. Historically, land surface schemes parameterize soil moisture stress based on shallow soils and incorrectly capture seasonal cycles in the Amazon. Following o...

Rainfall-runoff processes in a small oil palm catchment (8.2 ha) in Johor, Malaysia were examined. Storm hydrographs show rapid responses to rainfall with a short time to peak. The estimated initial hydrologic loss for the oil palm catchment is 5 mm. Despite the low initial loss, the catchment exhibits a high proportion of baseflow, approximately 54% of the total runoff. On an event basis, the ...

[1] Representation of model input uncertainty is critical in ensemble‐based data assimilation. Monte Carlo sampling of model inputs produces uncertainty in the hydrologic state through the model dynamics. Small Monte Carlo ensemble sizes are desirable because of model complexity and dimensionality but potentially lead to sampling errors and correspondingly poor representation of probabilistic s...

There have been many studies of hydrologic processes and scale. However, some researchers have found that predictions from hydrologic models may not be improved by attempting to incorporate the understanding of these processes into hydrologic models. This paper quantifies the effect of simplifying watershed geometry and averaging the parameter values on simulations generated using the KINEROS2 ...

Recently, authors have theorized that invasive species prevention is more cost-effective than control in protecting ecosystem services. However, quantification of the effectiveness of prevention is rare because experiments at field scales are expensive or infeasible. We therefore used structured expert judgment to quantify the efficacy of 17 proposed strategies to prevent Asian carp invasion of...

Emerging problems of environmental change and of long range hydrologic forecasting demand knowledge of the hydrologic cycle at global rather than catchment scale. Changes in atmosphere and/or landscape characteristics modify the earth's metabolism through changes in its biogeochemical cycles. The most basic of these is the water cycle which directly affects the global circulation of both atmosp...