NWSRFS CALIBRATION PARAMETER SELECTION AND GEOLOGIC REASONING: PACIFIC NORTHWEST CASES1

ABSTRACT: The National Weather Service River Forecast System (NWSRFS) is the new hydrologic prediction model for the National Weather Service (NWS) and provides guidance to meteorologists who issue NWS Flood Warnings to the public. The primary submodel within NWSRFS is the Sacramento Soil Moisture Accounting (SAC-SMA) model, which predicts surface runoff as a function of meteorological, geological, and soil data calibrated over a watershed. The research presented here focuses on a different approach to NWSRFS calibrations: greater utilization of geologic and soil data, in order to give the model better predictive capability. Geologic understanding can create better insights for the initial estimation and subsequent adjustment of SAC-SMA parameters. Fifteen calibrated Pacific Northwest drainages reveal a variety of hydrogeologic responses. For example, results for the Mount Rainier drainages show the complex interaction between active glaciers, impermeable volcanic surfaces, and glacial sedimentary valleys. Unweathered volcanic terrains show flashy peak flows, fast flow recessions, and low baseflow. Sedimentary terrains display subdued peak flows, slow flow recessions, and higher baseflow. Operational implementation of these calibrations at the NWS's Northwest River Forecast Center has yielded more accurate predictive results since 1995. NWS hydrologic forecasters nationwide could benefit from using drainage basin geologic characteristics in understanding and improving model calibrations and real time forecasts.     

Towards Real‐Time Continental Scale Streamflow Simulation in Continuous and Discrete Space

The National Weather Service (NWS) forecasts floods at approximately 3,600 locations across the United States (U.S.). However, the river network, as defined by the 1:100,000 scale National Hydrography Dataset‐Plus (NHDPlus) dataset, consists of 2.7 million river segments. Through the National Flood Interoperability Experiment, a continental scale streamflow simulation and forecast system was implemented and continuously operated through the summer of 2015. This system leveraged the WRF‐Hydro framework, initialized on a 3‐km grid, the Routing Application for the Parallel Computation of Discharge river routing model, operating on the NHDPlus, and real‐time atmospheric forcing to continuously forecast streamflow. Although this system produced forecasts, this paper presents a study of the three‐month nowcast to demonstrate the capacity to seamlessly predict reach scale streamflow at the continental scale. In addition, this paper evaluates the impact of reservoirs, through a case study in Texas. Validation of the uncalibrated model using observed hourly streamflow at 5,701 U.S. Geological Survey gages shows 26% demonstrate PBias ≤ |25%|, 11% demonstrate Nash‐Sutcliffe Efficiency (NSE) ≥ 0.25, and 6% demonstrate both PBias ≤ |25%| and NSE ≥ 0.25. When evaluating the impact of reservoirs, the analysis shows when reservoirs are included, NSE ≥ 0.25 for 56% of the gages downstream while NSE ≥ 0.25 for 11% when they are not. The results presented here provide a benchmark for the evolving hydrology program within the NWS and supports their efforts to develop a reach scale flood forecasting system for the country.     

Long‐Term High‐Resolution Radar Rainfall Fields for Urban Hydrology

Accurate records of high‐resolution rainfall fields are essential in urban hydrology, and are lacking in many areas. We develop a high‐resolution (15 min, 1 km²) radar rainfall data set for Charlotte, North Carolina during the 2001‐2010 period using the Hydro‐NEXRAD system with radar reflectivity from the National Weather Service Weather Surveillance Radar 1988 Doppler weather radar located in Greer, South Carolina. A dense network of 71 rain gages is used for estimating and correcting radar rainfall biases. Radar rainfall estimates with daily mean field bias (MFB) correction accurately capture the spatial and temporal structure of extreme rainfall, but bias correction at finer timescales can improve cold‐season and tropical cyclone rainfall estimates. Approximately 25 rain gages are sufficient to estimate daily MFB over an area of at least 2,500 km², suggesting that robust bias correction is feasible in many urban areas. Conditional (rain‐rate dependent) bias can be removed, but at the expense of other performance criteria such as mean square error. Hydro‐NEXRAD radar rainfall estimates are also compared with the coarser resolution (hourly, 16 km²) Stage IV operational rainfall product. Stage IV is adequate for flood water balance studies but is insufficient for applications such as urban flood modeling, in which the temporal and spatial scales of relevant hydrologic processes are short. We recommend the increased use of high‐resolution radar rainfall fields in urban hydrology.     

A COMPARISON OF GEOSTATISTICAL METHODOLOGIES USED TO ESTIMATE SNOW WATER EQUIVALENT1

ABSTRACT: The need to monitor and forecast water resources accurately, particularly in the western United States, is becoming increasingly critical as the demand for water continues to escalate. Consequently, the National Weather Service (NWS) has developed a geostatistical model that is used to obtain areal estimates of snow water equivalent (the thtal water content in all phases of the snowpack), a major source of water in the West. The areal snow water equivalent estimates are used to update the hydrologic simulation models maintained by the NWS and designed to produce extended streamflow forecasts for river systems throughout the United States. An alternative geostatistical technique has been proposed to estimate snow water equivalent. In this research, we describe the two methodologies and compare the accuracy of the estimates produced by each technique. We illustrate their application and compare their estimation accuracy using snow data collected in the North Fork Clearwater River basin in Idaho.     

A SURVEY OF THE U.S. NATIONAL PRECIPITATION NETWORK1

ABSTRACT: Numbers and record lengths of precipitation stations were surveyed in the conterminous United States using climatological data published in 1975 by the National Weather Service (NWS). The total numbers of nonrecording (8247) and recording (3036) gages were about the same as in the 1940s and less than in the late 1950s; about 70 percent of the nonrecording gages have record lengths of 25 years or more. State network densities were increased exponentially with population density and long term precipitation average. Except for a few states, precipitation stations maintained by the NWS are adequate in numbers to ensure a 95 percent statistical probability that state sample means will estimate true means within ± 5 percent.     

Conceptual Framework for the National Flood Interoperability Experiment

The National Flood Interoperability Experiment is a research collaboration among academia, National Oceanic and Atmospheric Administration National Weather Service, and government and commercial partners to advance the application of the National Water Model for flood forecasting. In preparation for a Summer Institute at the National Water Center in June‐July 2015, a demonstration version of a near real‐time, high spatial resolution flood forecasting model was developed for the continental United States. The river and stream network was divided into 2.7 million reaches using the National Hydrography Dataset Plus geospatial dataset and it was demonstrated that the runoff into these stream reaches and the discharge within them could be computed in 10 min at the Texas Advanced Computing Center. This study presents a conceptual framework to connect information from high‐resolution flood forecasting with real‐time observations and flood inundation mapping and planning for local flood emergency response.     

FLOOD ROUTING THROUGH A FLAT,COMPLEX FLOODPLAIN USING A ONE-DIMENSIONAL UNSTEADY FLOW COMPUTER PROGRAM1

ABSTRACT: The routing of flood waves through the Central Basin of the Passaic River in New Jersey is complex because of flat gradients and flow reversals. The one-dimensional unsteady flow program DWOPER, developed by the National Weather Service, was used to simulate flood wave movement through the Basin. A historical event was used for calibration and two synthetic events were simulated. Boundary conditions consisted of discharge hydrographs at inflow points to the study area, local flow hydrographs at interior points, and a stage discharge relation for flow over the crest of a diversion dam at the basin outlet. Manning's n values were adjusted based on stage and discharge data for the historical event; however, verification data were not available for events comparable in magnitude to the synthetic events. Aspects of the investigation reported include techniques for characterizing the flow system, model calibration, techniques for representing a tunnel diversion, and simulation results.     

PROBABLE MAXIMUM FLOOD ESTIMATION-EASTERN UNITED STATES1

In 1982, the National Weather Service (NWS) published criteria for developing the spatial and temporal precipitation distribution characteristics of Probable Maximum Storms. The criteria, which are intended for use in the United States east of the 105th meridian, involve four variables: (1) location of the storm center, (2) storm-area size, (3) storm orientation, and (4) temporal arrangement of precipitation amounts. A computer program has been developed which applies the NWS criteria to produce hyetographs of spatially-averaged precipitation for a basin, or for each subbasin if the basin is subdividided. The basis and operational characteristics of the program are described, and an application is illustrated in which the program is used in conjunction with a precipitation-runoff simulation program (HEC-1) to compute a Probable Maximum Flood.     

A HYDROCLIMATOLOGICAL ANALYSIS OF THE RED RWER OF THE NORTH SNOWMELT FLOOD CATASTROPHE OF 19971

ABSTRACT: The flood hydroclimatology of the Grand Forks flood of April 1997, the most costly flood on a per capita basis for a major metropolitan area in United States history, is analyzed in terms of the natural processes that control spring snowmelt flooding in the region. The geomorphological characteristics of the basin are reviewed, and an integrated assessment of the hydroclimatological conditions during the winter of 1996 to 1997 is presented to gain a real‐world understanding of the physical basis of this catastrophic flood event. The Grand Forks flood resulted from the principal flood‐producing factors occurring at either historic or extreme levels, or at levels conducive to severe flooding. Above normal fall precipitation increased the fall soil moisture storage and reduced the spring soil moisture storage potential. A concrete frost layer developed that effectively reduced the soil infiltration capacity to zero. Record snowfall totals and snow cover depths occurred across the basin because of the unusual persistence of a blocking high circulation pattern throughout the winter. A severe, late spring blizzard delayed the snowmelt season and replenished the snow cover to record levels for early April. This blizzard was followed by a sudden transition to an extreme late season thaw due to the abrupt breakdown of the blocking circulation pattern. The presence of river ice contributed to backwater effects and affected the timing of tributary inflows to the main stem of the Red River. Only the absence of spring rains prevented an even more catastrophic flood disaster from taking place. This paper contributes to our understanding of the flood hydroclimatology of catastrophic flood events in an unusual flood hazard region that possesses relatively flat terrain, a north‐flowing river, and an annual peak discharge time series dominated by spring snowmelt floods.     

Time Series Analysis of Nebraska Daily Rainfall Data to Simulate Atrazine Runoff1

Abstract: Measured atrazine concentrations in Nebraska surface water have been shown to exceed water‐quality standards, posing risks to humans and to the ecosystem. To assess this risk, atrazine runoff was simulated at the field‐scale in Nebraska based on the pesticide component of the AGNPS model. This project’s objective was to determine the frequency that the atrazine concentration at the field outlet exceeded three different atrazine water‐quality criteria. The simulation was conducted for different farm management practices, soil moisture conditions, and five Nebraska topographic regions. If the criteria were exceeded, a risk to the drinking water consumer or freshwater aquatic life was hypothesized to exist. Three pesticide fate and transport processes were simulated with the model. Degradation was simulated using first‐order kinetics. Adsorption/desorption was modeled assuming a linear soil‐water partitioning coefficient. Advection (runoff) was based primarily on the USDA‐NRCS curve number method. Daily rainfall from the National Weather Service was used to compute the soil moisture conditions for the 1985‐2000 growing seasons. After each runoff event, the pesticide runoff concentration was compared with each of the three atrazine water‐quality criteria. The results show that environmental receptors (i.e., freshwater aquatic species) are exposed to unacceptable atrazine runoff concentrations in 20‐50% of the runoff events.     

Assessing Effectiveness of National Flood Policy Through Spatiotemporal Monitoring of Socioeconomic Exposure1

Abstract: After a century of evolving flood policies, there has been a steady increase in flood losses, which has partly been driven by development in flood prone areas. National flood policy was revised in 1994 to focus on limiting and reducing the amount of development inside the 100‐year floodplain, with the goal of decreasing flood losses, which can be measured and quantified in terms of population and property value inside the 100‐year floodplain. Monitoring changes in these measurable indicators can inform where and how effective national floodplain management strategies have been. National flood policies are restricted to the spatial extent of the 100‐year floodplain, thus there are no development regulations to protect against flooding adjacent to this boundary. No consistent monitoring has been undertaken to examine the effect of flood policy on development immediately outside the 100‐year floodplain. We developed a standardized methodology, which leveraged national data to quantify changes in population and building tax value (exposure). We applied this approach to counties in North Carolina to assess (1) temporal changes, before and after the 1994 policy and (2) spatial changes, inside and adjacent to the 100‐year floodplain. Temporal results indicate the Piedmont and Mountain Region had limited success at reducing exposure within the 100‐year floodplain, while the Coastal Plain successfully reduced exposure. Spatially, there was a significant increase in exposure immediately outside the 100‐year floodplain throughout North Carolina. The lack of consistent monitoring has resulted in the continuation of this unintended consequence, which could be a significant driver of increased flood losses as any flood even slightly higher than the 100‐year floodplain will have a disproportionately large impact since development is outside the legal boundary of national flood policy.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Using Steady‐State Backwater Analysis to Predict Inundated Area from National Water Model Streamflow Simulations

National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts for 2.7 million reaches in the National Hydrography Dataset for continental United States (U.S.). NWM uses Muskingum–Cunge channel routing, which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain more accurate estimates of streamflow and stage in rivers, especially for applications such as flood‐inundation mapping. Here, we used a steady‐state backwater version of Simulation Program for River NeTworks (SPRNT) model. We evaluated SPRNT’s and NWM’s abilities to predict inundated area for the record flood of Hurricane Matthew in October 2016. The Neuse River experienced record‐breaking floods and was well‐documented by U.S. Geological Survey. Streamflow simulations from NWM retrospective analysis were used as input for the SPRNT simulation. Retrospective NWM discharge predictions were converted to stage. The stages (from both SPRNT and NWM) were utilized to produce flood‐inundation maps using the Height Above Nearest Drainage method which uses the local relative heights to find out the local draining potentials and provide spatial representation of inundated area. The inundated‐area accuracies for NWM and SPRNT (based on comparison to a remotely sensed dataset) were 65.1% and 67.6%, respectively. These results show using steady‐state SPRNT results in a modest improvement of inundation‐forecast accuracy compared to NWM.     

NEAR REAL-TIME MAPPING OF THE 1975 MISSISSIPPI RIVER FLOOD IN LOUISIANA USING LANDSAT IMAGERY1

ABSTRACT: The project described in this report was undertaken by the Louisiana State Planning Office to establish the extent of backwater flooding in Louisiana in April 1975. Band 7 Landsat imagery, enlarged to a scale of 1:250,000 was used to visually identify flooded areas. Inundated areas were delineated on overlays keyed to 1:250,000 U.S. Geological Survey topographic quadrangles. Tabular data identifying acres flooded, according to land use type, were derived by merging the flood map overlays with computerized 1972 land use data. Approximately 1.12 million acres of the state were inundated by flood waters. The total acreage and land use types affected by flooding were determined within 72 hours from the time the flood areas were imaged. Flooded maps were prepared for 26 parishes. Field observations were made by Louisiana Cooperative Extension Service county agents in order to determine the accuracy of parish flood maps and flood acreage figures by land use type. Results indicated that this was a fast, accurate, and relatively inexpensive method of compiling flood data for disaster planning and postflood analysis.     

A Faster and Economical Approach to Floodplain Mapping Using Soil Information

Flood inundation maps play a key role in assessment and mitigation of potential flood hazards. However, owing to high costs associated with the conventional flood mapping methods, many communities in the United States lack flood inundation maps. The objective of this study is to develop and examine an economical alternative approach to floodplain mapping using widely available soil survey geographic (SSURGO) database. In this study, floodplain maps are developed for the entire state of Indiana, and some counties in Minnesota, Wisconsin, and Washington states by identifying flood‐prone soil map units based on their attributes. For validation, the flood extents obtained from SSURGO database are compared with the extents from other floodplain maps such as the Federal Emergency Management Agency issued flood insurance rate maps (FIRMs), flood extents observed during past floods, and flood maps derived using digital elevation models. In general, SSURGO‐based floodplain maps (SFMs) are largely in agreement with other flood inundation maps. Specifically, the floodplain extents from SFMs cover 78‐95% area compared to FIRMs and observed flood extents. Thus, albeit with a slight loss in accuracy, the SSURGO approach offers an economical and fast alternative for floodplain mapping. In particular, it has potentially high utility in areas where no detailed flood studies have been conducted.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

OPTIMIZATION OF TRANSPORTATION NETWORKS DURING URBAN FLOODING1

ABSTRACT: In this paper a numerical model for flood propagation in urban areas is proposed. It has been applied to evaluate flooding hydraulic characteristics in terms of potential flood elevations, depths, and inundated areas. Furthermore, the algorithm efficiency and the consequent reduced computation time allow the use of the hydraulic model as a part of a more complex system for civil protection actions, planning, and management. During flood events, the transportation network plays a main role both in rescuing people when they are more vulnerable and in moving people and materials from and toward affected areas. The reduced efficiency of this transportation network is evaluated based on a least‐flood‐risk path‐finding algorithm. The results of a case study concerning the northern part of the city of Rome, show that the numerical model for unsteady flow in open channel networks achieves the proposed aims. It has proven to be able to describe the flood hydraulic characteristics and to be suitable for real‐time flood emergency management in urban areas.     

A High‐Resolution National‐Scale Hydrologic Forecast System from a Global Ensemble Land Surface Model

Warning systems with the ability to predict floods several days in advance have the potential to benefit tens of millions of people. Accordingly, large‐scale streamflow prediction systems such as the Advanced Hydrologic Prediction Service or the Global Flood Awareness System are limited to coarse resolutions. This article presents a method for routing global runoff ensemble forecasts and global historical runoff generated by the European Centre for Medium‐Range Weather Forecasts model using the Routing Application for Parallel computatIon of Discharge to produce high spatial resolution 15‐day stream forecasts, approximate recurrence intervals, and warning points at locations where streamflow is predicted to exceed the recurrence interval thresholds. The processing method involves distributing the computations using computer clusters to facilitate processing of large watersheds with high‐density stream networks. In addition, the Streamflow Prediction Tool web application was developed for visualizing analyzed results at both the regional level and at the reach level of high‐density stream networks. The application formed part of the base hydrologic forecasting service available to the National Flood Interoperability Experiment and can potentially transform the nation's forecast ability by incorporating ensemble predictions at the nearly 2.7 million reaches of the National Hydrography Plus Version 2 Dataset into the national forecasting system.     

IMPROVED RAINFALL/RUNOFF ESTIMATES USING REMOTELY SENSED SOIL MOISTURE1

ABSTRACT: Remotely sensed soil moisture data measured during the Southern Great Plains 1997 (SGP97) experiment in Oklahoma were used to characterize antecedent soil moisture conditions for the Soil Conservation Service (SCS) curve number method. The precipitation‐adjusted curve number and the soil moisture were strongly related (r²= 0.70). Remotely sensed soil moisture fields were used to adjust the curve numbers and the runoff estimates for five watersheds, in the Little Washita watershed; the results ranged from 2.8 km² to 601.6 km². The soil moisture data were applied at two spatial scales, a finer one (800 m) measuring spatial resolution and a coarser one (28 km). The root mean square error (RMSE) and the mean absolute error (MAE) of the runoff estimated by the standard SCS method was reduced by nearly 50 percent when the 800 m soil moisture data were used to adjust the curve number. The coarser scale soil moisture data also significantly reduced the error in the runoff predictions with 41 percent and 28 percent reductions in MAE and RMSE, respectively. The results suggest that remote sensing of soil moisture, when combined with the SCS method, can improve rainfall runoff predictions at a range of spatial scales.     

FLOOD HAZARD STUDIES IN THE MISSISSIPPI RIVER BASIN USING REMOTE SENSING1

ABSTRACT. The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicate that ERTS-I is extremely useful as a regional tool for flood management. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. The flood prone areas delineated on these maps correspond to areas that would be inundated by significant flooding (approximately the 100 year flood). The flood prone area boundaries were generally in agreement with flood hazard maps produced by the U. S. Army Corps of Engineers and U. S. Geological Survey although the latter are somewhat more detailed because of their larger scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.