Haiti-Dominican Republic Flash Flood Guidance (HDRFFG) System: Development of System Products

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Haiti-Dominican Republic Flash Flood Guidance (HDRFFG) System: Development of System Products Theresa M. Modrick, PhD Hydrologic Research Center HDRFFG Initial Planning Meeting 07-09 Sep 2015 Santo Domingo, DR

HDRFFG System Products 1. Observed Precipitation 2. Hydrologic State 3. Forecast Precipitation 2

HDRFFG System Products: Precipitation OBSERVED PRECIPITATION: How much precipitation has fallen MAP: Mean areal precipitation The average precipitation (observed or forecast) over each watershed. 3

HDRFFG System Products: Precipitation FORECAST PRECIPITATION: How much precipitation is expected based on NWP model QPF. 4

HDRFFG System Products 1. Observed Precipitation 2. Hydrologic State 3. Forecast Precipitation 5

Why is Soil Moisture Important? Georgakakos et al., WRR 31(3), 210-220, 1995. 6

ASM: Average Soil Moisture Key Definitions An estimate of the level of saturation (fraction) in the upper soil layer. This is computed by the model. Forecasters may see changes as precipitation falls and basins (or groups of basins) become more saturated. 7

Key Definitions Flash Flood Guidance (FFG): The amount of rainfall of a given duration and over a given catchment that is just enough to cause bankfull conditions at the outlet of the draining stream FFG Bankfull Flow: flow level in stream associated with the transition from main/active channel to overbank or flood plain. This is level of initiation of flooding (not necessarily damage level). Bankfull Flow 8

HDRFFG System Products Flash Flood Threat (FFT): System computed difference between the MAP and FFG values. 9

Key Technical Components for Flash Flood Guidance Systems Real-time Precipitation Input Satellite Rainfall Radar (as available) Gauge (as available) Rainfall Data Processing Quality Control Merging Bias Adjustment Snow Model Snow Cover Temperature Flash Flood Guidance Model Soil Moisture Model Evapotranspiration (Climatological) Flash Flood Guidance Threshold Runoff Model Forecaster Input Flash Flood Threat Rainfall Forecasts (Mesoscale Model) Spatial GIS Data Analysis Basin Delineation Parameter Estimation (Terrain, LULC, Soils) 1010

HDRFFG System Products Flash Flood Guidance Systems need up-to-date high-quality estimates of precipitation to assess current flash flood potential. 11

Satellite Precipitation HydroEstimator (GHE) Remotely-sensed precipitation estimates provide good spatial coverage and detail. In situ observations (rain gauges) provide ground truth but often have sparse coverage. NOAA/NESDIS Hydro-Estimator 24-hr rainfall ending 31-Aug-2016 @ 12 UTC Satellite estimates since late 1970s; Hydro-Estimator since 2002; GHE operational in 2012. Provide critical data in data sparse regions! Infrared (IR) based (10.7 µm) **Short latency**(< ½ hour) ~4 km resolution GHE: Rainfall rate based on Cloud Top Brightness Temperature (indirect measurement) 12

Multi-Spectral Satellite Precipitation for FFG Systems CMORPH is based on measurements of microwave scattering from raindrops. - measure of the hydrometeors in clouds - still not observation of rainfall at surface - ~8 km resolution - 18-26 hr latency in operations 13

Multi-Spectral Satellite Precipitation for FFG Systems HRC effort to combine IR-based GHE rainfall with MW-based CMORPH rainfall HRC-developed method which: (a) compares IR-based GHE and MW-based CMORPH for period (2-3 days) up to last CMORPH observation, (b) develops an adjustment factor based on differences within region, (c) applies adjustment to GHE up to current observation. FFGS Product MWGHE Example from South East Europe (SEEFFGS) 14

Merged MAP Product Example from Black Sea Middle East (BSMEFFGS) Merged MAP is the best estimate of Mean Areal Precipitation over each small watershed for previous 1-, 3-, 6- and 24- hour periods. - Satellite - Real-time gauges - Radar (if available) * Includes bias adjustment 15

Bias Adjustment for Satellite Precipitation Bias may exist in the remotely sensed precipitation estimates relative to gauges. Bias should be removed before inputting to hydrologic models. Vastly different scales of satellite pixel and rain gauge area Orography organizes surface rainfall according to prevailing winds Satellite estimates do not directly measure rainfall at surface There may be significant misregistration errors in satellite data Satellite Pixel, R SAT Raingauge, R G (xo,yo) 16

Bias Adjustment for Satellite Precipitation REGION A Sat Pixel 1 Gauge 1 Region 3 (Adriatic Coastal) Wet Season # Gauge/Pixel Pairs = 36 Gauge 2 Sat Pixel 2 Sat Pixel 3 Gauge 3 Sat Pixel N Gauge N Log Bias: ββ tt = ln NN GG jj=1 RR GG jj, tt /NNNN NN GG jj=1 RR SSSSSS jj, tt /NNNN Two bias adjustments may be made: climatological and real-time. 17

Climatological Bias Adjustment Considers long-term bias in satellite precipitation estimates based on historical data from satellite and raingauge network. Regions of uniform hydroclimatology, terrain and gauge density Analysis is done on monthly or seasonal basis (depending on data record) Bias Factor computed from mean monthly values Bias Factor computed based on probability matching We gather historical raingauge data to do initial analysis, then train forecasters to do this analysis, so they may repeat as additional years of data are available. 18

Dynamic Bias Adjustment Considers event (short-term) adjustment based on real-time gauge reports Employs Kalman Filter approach Minimum number of gauge/satellite pixel pairs reporting over consecutive time steps β t = n N g j= 1 N g j= 1 Rg (, t j) Rs (, t j) Gauge data quality control is important! β = β + w t t t + 1 + 1 z = β + v t t t + 1 + 1 + 1 Example from South East Europe (SEEFFGS) 19

Historical Analysis: 2006 2010 Limited Gauges Bias Adjustment for HDRFFG Dynamic Bias Adjustment is disengaged as real-time stations are no longer reporting. 20

Key Technical Components for Flash Flood Guidance Systems Real-time Precipitation Input Satellite Rainfall Radar (as available) Gauge (as available) Rainfall Data Processing Quality Control Merging Bias Adjustment Snow Model Snow Cover Temperature Flash Flood Guidance Model Soil Moisture Model Evapotranspiration (Climatological) Flash Flood Guidance Threshold Runoff Model Forecaster Input Flash Flood Threat Rainfall Forecasts (Mesoscale Model) Spatial GIS Data Analysis Basin Delineation Parameter Estimation (Terrain, LULC, Soils) 2121

Need for Soil Water Accounting What happens after rain falls? Hydrologic Components of FFG System account for land surface processes in production of flash floods. infiltration of rainfall into soil and storage of soil water accumulation and ablation of snow, and snow melt contribution to soil production of runoff into channels evapotranspiration From BBC news 22

HDRFFG System Products Example from Black Sea Middle East (BSMEFFGS) 23

Soil Model for HDRFFG A conceptual hydrologic model is used for soil water modeling: Sacramento Soil Moisture Accounting Model (SAC-SMA) to estimate ability of land surface to absorb and hold moisture. A two-layer conceptual model representing the movement of soil water through a vertical, homogeneous soil column 24

Soil Model for HDRFFG Schematic of Sacramento SMA Model INPUT: Precipitation (or Rain+Snow melt) Potential Evapotranspiration Various representations of runoff: saturation excess infiltration excess combined runoff PARAMETERIZATION: 15 model parameters (capacities, withdrawal rates, percolation) Initial parameters based on soils and land cover 25

Effect of Soil Classification on Runoff Production 26

Relating Soils Characteristics to Hydraulic Properties Figures from Brady, N.C., 1974: The nature and properties of soils. McMillan Publ. Co., NY 27

Sacramento SMA Model Parameterization Soil Class θ s (m 3 /m 3 ) θ f (m 3 /m 3 ) θ m (m 3 /m 3 ) K s (m/h) α σ Ks (m/h) Sand 0.34 0.09 0.015 0.168 2.79 0.062 Loamy Sand 0.42 0.16 0.05 0.050 4.26 0.082 Sandy Loam 0.43 0.21 0.07 0.019 4.74 0.119 Loam 0.44 0.25 0.095 0.012 5.25 0.108 Silty Loam 0.48 0.29 0.11 0.010 5.33 0.090 28

Example Soil Model Output: Site-Specific Validation Simulation for Illinois River Basin in Oklahoma, U.S.A - - - Simulation Westville, OK Reasonably good reproduction of depth integrated soil water deficit 29

Example SAC-SMA Model Parameterization for HDRFFG Upper Layer Capacity 30

HDRFFG System Product: ASM ASM: is the soil saturation fraction in the upper model soil layer (most relevant for flash flood occurrence) 2016-08-01 12 UTC 2016-08-01 18 UTC 2016-08-02 00 UTC 31

HDRFFG System Products Example from Black Sea Middle East (BSMEFFGS) 32

Key Concepts Threshold Runoff: Matching of peak surface runoff to bankfull flow (as an indicator of the initiation of flooding conditions) Links geomorphology to channel geometry (avoids calibration) Flash Flood Guidance: Rainfall threshold concept, familiar in operational meteorological forecasting. Decouples soil moisture deficit from surface runoff computations Coordinated hydro-meteorologic forecast operations 33

Definition of Threshold Runoff Threshold Runoff is defined as the amount of effective rainfall of a given duration falling over a watershed that is just enough to cause bankfull conditions at the outlet of the draining stream. Effective rainfall is the residual amount after accounting for all losses such as interception and soil moisture storage. Effective rainfall contributes directly to runoff production. 34

Threshold runoff represents the storage capacity of the stream to accept catchment runoff to a level of minor flooding defined at bankfull. Threshold Runoff, R, = nonlinear function of catchment properties (A,L,R L ) and channel cross-section characteristics (B b, D b, S c ). Definition of Threshold Runoff 35

Estimation of Threshold Runoff Watershed properties (A, L) may be estimated from processing of digital elevation data (DEM). Channel cross sections are not resolved with current global DEMs. Bankfull condition may be identified using morphological field evidence during local stream surveys. Bankfull cross-section dimensions vary with catchment size (Luna, 1994). Local survey data may be used to develop regional relationships: B b = αa γ D b = εa λ 36

Threshold Runoff Estimates for HDRFFG (1) Define watershed boundaries (based on 90-m SRTM DEM) (2) Compute watershed properties (A, L, S) (3) No local channel survey data available. Utilized satellite imagery and data from Puerto Rico to develop regional relationships for cross-section properties. (4) Estimate channel cross-section from regional regressions (5) Compute threshold runoff 1-HOUR TR 6-HOUR TR Threshold Runoff is a one-time calculation, a characteristic property, for a given watershed. 37

Definition of Flash Flood Guidance Flash Flood Guidance (FFG): The amount of rainfall of a given duration and over a given catchment that is just enough to cause bankfull conditions at the outlet of the draining stream. FFG is computed on a real-time basis considering up-to-date soil water content. FFG FFG is updated every hour in HDRFFG (currently) and computed for rainfall durations of 1-, 3-, and 6-hours. 38

Relationship between Threshold Runoff and FFG A) What if scenario For a given watershed Rainfall Runoff 39 39

Relationship between Threshold Runoff and FFG For a given watershed Rainfall FFG model component defines this relationship analytically for each small watershed, at each time step with updated soil moisture condition. Runoff 40 40

From Threshold Runoff and Soil Moisture to FFG Model Forecast Run Time (hourly) For a given watershed Soil Moisture Deficit, t i Soil Moisture Deficit, t i+1 41 41

HDRFFG System Product: FFG FFG: is the amount of precipitation of a given duration over a watershed necessary to cause bankfull conditions at the watershed outlet. FFG is computed for rainfall durations of 1, 3 and 6-hours. FFG-03hr for 2016-08-01 00 UTC FFG-06hr for 2016-08-01 00 UTC FFG-03hr for 2016-08-02 00 UTC 42

HDRFFG System Products Informational Products: FFTs Example from Black Sea Middle East (BSMEFFGS) 43

Example SAC-SMA Model Parameterization for HDRFFG Potential for flash flooding is increased when PRECIPITATION > FFG. Flash Flood Threat, FFT, defined: FFT = MAP - FFG FFFT-01hr for 2016-05-04 00 UTC IFFT-03hr for 2016-05-08 00 UTC FFT provides indication of regions of potential concern. Color bar provides magnitude of FFT. Like FFG, FFT products for computed for 1, 3, and 6-hour durations. 44

HDRFFG System Products: FFTs Different FFT products are provided, based on observed or forecasted precipitation and timing. - IFFT: imminent, based on observed precipitation that has fallen. Flash flooding may be occurring! - PFFT: forecast of persistence IF rainfall continues at current rate - FFFT: based on forecast precipitation. 45

Flash Flood Threat Products FFFT-03hr for 2016-05-08 00 UTC Operational forecasters recognize FFG System products and precipitation forecasts carry uncertainty, and must evaluate the current situation and forecast. FFT products are *not* intended to be the forecast, but are system indicators of potential concern. The role of the forecaster in evaluating available information is critical. 46

Overview of the Development of FFG System Products In summary: FFG Systems are designed to provide operational hydro-meteorological forecasters with quality information relevant to the assessment of flash flood potential toward the generation of warnings. Flash flood guidance concept provides estimate of the amount of precipitation necessary to produce flooding condition. FFG System ingest high resolution satellite estimates of precipitation in real time with short latency. Development of the technical and modeling components was reviewed. This included: - precipitation data ingest, quality control, and adjustment - accounting of the hydrologic state of the land surface and its ability to accept precipitation - estimation of threshold runoff as an indicator of channel storage - system-computed indications of regions with precipitation exceeding flash flood guidance 47

Overview of the Development of FFG System Products THANK YOU 48

FFG System Products in Context of End-to-End Chain 49

Estimation of Threshold Runoff Under assumption that watersheds respond linearly to rainfall excess, threshold runoff found by equating peak catchment runoff to flow at outlet associated with flooding. Carpenter et al., J. Hydrology, 1999. Q p = q pr R A Flooding flow, Q p = bankfull flow as calculated from hydraulic principles (Mannings steady uniform resistance formula). Q p = f(channel cross-sectional characteristics: B b, D b, S c ) Peak of unit hydrograph is based on Geomorphologic Instantaneous Unit Hydrograph (GIUH) theory. Unit hydrograph peak response, q pr = f(catchment & channel characteristics, rainfall rate) Threshold Runoff, R = nonlinear function of catchment and channel characteristics (A,L, R L, B b, D b, S c ) 50