Applying SMOS soil moisture data into the National Weather Service (NWS)’s Research Distributed Hydrologic Model (HL-RDHM) for flash flood guidance application

Abstract Quantifying uncertainty associated with flash flood warning or forecast systems is required to enable informed decision making by those responsible for operation and management of natural hazard protection systems. The current system used by the U.S. National Weather Service (NWS) to issue flash-flood warnings and watches over the Unites States is a purely deterministic system. The authors propose a simple approach to augment the Flash Flood Guidance System (FFGS) with uncertainty propagation components. The authors briefly discuss the main components of the system, propose changes to improve it, and allow accounting for several sources of uncertainty. They illustrate their discussion with examples of uncertainty quantification procedures for several small basins of the Illinois River basin in Oklahoma. As the current FFGS is tightly coupled with two technologies, that is, threshold-runoff mapping and the Sacramento Soil Moisture Accounting Hydrologic Model, the authors discuss both as sources of uncertainty. To quantify and propagate those sources of uncertainty throughout the system, they develop a simple version of the Sacramento model and use Monte Carlo simulation to study several uncertainty scenarios. The results point out the significance of the stream characteristics such as top width and the hydraulic depth on the overall uncertainty of the Flash Flood Guidance System. They also show that the overall flash flood guidance uncertainty is higher under drier initial soil moisture conditions. The results presented herein, although limited, are a necessary first step toward the development of probabilistic operational flash flood guidance forecast-response systems.

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Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

Hydrology and Earth System Sciences ◽

10.5194/hess-15-3809-2011 ◽

2011 ◽

Vol 15 (12) ◽

pp. 3809-3827 ◽

Cited By ~ 15

Author(s):

A. Atencia ◽

L. Mediero ◽

M. C. Llasat ◽

L. Garrote

Keyword(s):

Sensitivity Analysis ◽

Time Resolution ◽

Heavy Rainfall ◽

Flash Flood ◽

Probabilistic Approach ◽

Great Influence ◽

Hydrologic Model ◽

Radar Rainfall ◽

Distributed Hydrologic Model ◽

Correction Technique

Abstract. The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

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An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

Advances in Geosciences ◽

10.5194/adgeo-44-89-2017 ◽

2017 ◽

Vol 44 ◽

pp. 89-100 ◽

Cited By ~ 8

Author(s):

Luca Cenci ◽

Luca Pulvirenti ◽

Giorgio Boni ◽

Marco Chini ◽

Patrick Matgen ◽

...

Keyword(s):

Soil Moisture ◽

Data Assimilation ◽

Spatial Resolution ◽

Temporal Resolution ◽

Hydrological Model ◽

High Spatial Resolution ◽

Flash Flood ◽

Soil Moisture Data ◽

Time Period ◽

The Impact

Abstract. The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM–DA framework for flash flood risk mitigation.

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Flash Flood Forecasting for Ungauged Locations with NEXRAD Precipitation Data, Threshold Frequencies, and a Distributed Hydrologic Model

World Environmental and Water Resources Congress 2009 ◽

10.1061/41036(342)622 ◽

2009 ◽

Cited By ~ 2

Author(s):

Brian A. Cosgrove ◽

Seann Reed ◽

Feng Ding ◽

Yu Zhang ◽

Zhengtao Cui ◽

...

Keyword(s):

Flash Flood ◽

Flood Forecasting ◽

Hydrologic Model ◽

Precipitation Data ◽

Distributed Hydrologic Model ◽

Flash Flood Forecasting

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Effect of GPR-derived within-field soil moisture variability on the runoff response using a distributed hydrologic model

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-8947-2010 ◽

2010 ◽

Vol 7 (6) ◽

pp. 8947-8986 ◽

Cited By ~ 2

Author(s):

J. Minet ◽

E. Laloy ◽

S. Lambot ◽

M. Vanclooster

Keyword(s):

Soil Moisture ◽

High Resolution ◽

Spatial Variability ◽

Hydrologic Model ◽

Topographic Wetness Index ◽

Antecedent Soil Moisture ◽

Distributed Hydrologic Model ◽

Ground Penetrating ◽

Moisture Conditions ◽

Soil Moisture Variability

Abstract. The importance of the spatial variability of the antecedent soil moisture conditions on the runoff response is widely acknowledged in hillslope hydrology. Using a distributed hydrologic model, this paper aims at investigating the effects of soil moisture spatial variability on the runoff in various field conditions and at finding the soil moisture scenario that behaves the most closely as the measured soil moisture pattern in term of runoff hydrograph. Soil moisture was surveyed in ten different field campaigns using a proximal ground penetrating radar (GPR) that allowed to perform high-resolution (~m) mapping at the field scale (several ha). Based on these soil moisture measurements, seven scenarios of antecedent soil moisture were used to feed hydrological simulations and the resulting hydrographs were compared. The novelty of this work is to benefit from high-resolution soil moisture measurements using an advanced GPR in various soil moisture conditions. Accounting for the spatial variability of soil moisture resulted in a larger discharge than using a spatially constant soil moisture. The ranges of possible hydrographs were delineated by the extreme scenarios where soil moisture was directly and inversely arranged according to the topographic wetness index (TWI). These behaviours could be explained in terms of runoff contributing areas, with respect to their sizes and their relative locations within the field. The most efficient scenario for soil moisture appeared to be when soil moisture is directly arranged according to the TWI. This was related to the correlation of the measured soil moisture and the TWI. These observations generalised some of the statements pointed out in previous studies. Similar findings are thus expected under similar soil and rainfall forcing conditions.

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Validation of soil moisture simulation with a distributed hydrologic model (WetSpa)

Environmental Earth Sciences ◽

10.1007/s12665-012-1957-8 ◽

2012 ◽

Vol 69 (3) ◽

pp. 739-747 ◽

Cited By ~ 17

Author(s):

Mohsen Tavakoli ◽

Florimond De Smedt

Keyword(s):

Soil Moisture ◽

Hydrologic Model ◽

Distributed Hydrologic Model

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Development of a hydrologic model for a Canadian watershed

Canadian Journal of Civil Engineering ◽

10.1139/l78-013 ◽

1978 ◽

Vol 5 (1) ◽

pp. 126-134 ◽

Cited By ~ 27

Author(s):

G. W. Kite

Keyword(s):

Hydrologic Model ◽

Conclusive Evidence ◽

Hydrologic Models ◽

Forecast System ◽

National Weather Service ◽

Northern Ontario ◽

New Model ◽

Reservoir Regulation ◽

Spring Snowmelt ◽

Weather Service

Three large well-known hydrologic models, the Streamflow Synthesis and Reservoir Regulation, the National Weather Service River Forecast System, and the Saskatchewan River Model No. 6, were calibrated and verified on a 2000 km2 watershed in northern Ontario over two spring snowmelt periods. Although results obtained were adequate it was thought that a smaller simpler model could be designed that would give results at least as good with much less expenditure of time, money, and effort. Details of the relative performances of the three existing and one new model are given and comparative hydrographs are shown. Although use of the models on only one basin cannot provide conclusive evidence of the models' relative goodness, the results obtained do show significant differences between the models as well as certain advantages for the new model.

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