Geographical Database Development for the TxRR Surface Water Model
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Transcript of Geographical Database Development for the TxRR Surface Water Model
Geographical Database Development for the TxRR Surface Water Model
Richard Gu
Introduction of TxRR model
TxRR (Texas Rainfall-Runoff) Model:
Based on the Soil Conservation Service’s Curve Number Method to estimate the direct runoff from a precipitation event.
TxRR Model
Initial AbstractionPrecipitation P
Direct runoff QD
Base Flow QBStream FlowMaximum Soil
Moisture SMMAX
Soil Retention S
Soil Moisture SM
Percolation
Soil Moisture
The depletion process of the soil moisture:
SM2i=SM1i-1*exp(-mti)
SM2i: soil moisture right before the I-th precipitation
SM1i-1: soil moisture right after the I-1st precipitation
m: monthly depletion factor for the m-th month
ti: arrival time in days of the I-th precipitation
Soil Retention
Si=SMMAX-SM2iSi: soil retention
SMMAX: maximum soil moisture
Direct Runoff
QDi=Pei2/(Pei+Si)
Pei=Pi-Iai
Iai=abst1*SiQdi: direct runoff
Pei: effective precipitation
abst1: initial abstraction coefficient
New Soil Moisture
Soil moisture is renewed by the infiltration caused by new
precipitation. The renewal process is described by:
SM1i=SM2i+Fi
Fi=Pi-Iai-QDiSM1i: new soil moisture right after ith precipitation
Fi: infiltration
Base Flow
QB2=QB1*K t2-t1
K: recession constant
QB2, QB1: base flow at time t2, t1
t2-t1: the elapse time
Daily Streamflow Simulation
NDAYS=INT(Tb/24)+1
Tb=5Tp, Tp=12+Tl, Tl=*A 0.6
NDAYS: base time in days
Tb: base time
Tp: time to peak
Tl: lag time
A: drainage area
Monthly Depletion Factor & Parameter Optimization
• Important feature of TxRR model.
• Monthly depletion factor used for monthly streamflow simulation.
• Optimization based on the historical data.
GIS Data Preprocessing
• Goal: to prepare time-series streamflow & precipitation data for defined watershed.
• Sources data: historical data of USGS & NCDC stations.
• Sample area: Nueces Estuary.
• Tools: Arc/Info, CRWR-Vector, Arcview Geoprocessing & Spatial Analyst.
Sub_AREA% NUECES_ID WS_ID USGS_O_ID0.16% 1 21010 112329.72% 1 21010 104227.03% 1 21010 104118.45% 1 21010 104024.64% 1 21010 103995.27% 2 20005 11234.73% 2 20005 1042
100.00% 3 24830 112369.25% 4 24820 112330.75% 4 24820 104294.37% 5 22012 1042100.00% 6 24810 1123100.00% 7 0 112389.52% 8 22013 112310.48% 8 22013 10420.16% 9 22010 112353.04% 9 22010 104346.80% 9 22010 104231.04% 10 22011 11235.47% 10 22011 112363.49% 10 22011 1043100.00% 11 22014 112394.83% 12 1 11235.17% 12 1 1043
100.00% 13 24850 1123
NUECES_ID Sub_AREA% WS_ID NCDCSTAT_I1 2.00% 21010 20141 23.45% 21010 20151 74.55% 21010 56612 100.00% 20005 20143 100.00% 24830 20144 50.30% 24820 20144 32.29% 24820 20155 94.37% 22012 20156 60.66% 24810 20146 39.34% 24810 32107 13.43% 0 20147 86.57% 0 32108 49.78% 22013 20148 50.22% 22013 20159 100.00% 22010 201510 28.68% 22011 165110 4.31% 22011 201410 1.28% 22011 201410 37.63% 22011 201510 28.10% 22011 321011 66.67% 22014 201411 33.33% 22014 321012 100.00% 1 321013 100.00% 24850 3210
DSS databaseImplementation of Pre-processing
Source Data CD
Text file Arcview GIS
Rainfall data &Stream flow data
Spatial Informationof gages
DSS file
DSS import:DSSUTL
Watershed Region Definition
Develop Thiessen Polygons
Export we ighted ar ea percentage for ea ch ga ge. (gage::area %)
DSS
DSS
DSSMATH
Rainfall & stream flow, area%
NEW DSS file with Average rainfall & stream flow data for each watershed
DSPLAY
REPGEN
Customized Reports
Data Retrieval
TxRR Input File
Text file converter
DSPLAY Macro
DSPLAY Macro
Project Components
TxRR model: source code in FORTRAN
GIS: CRWR_Vector (Projection, Thiessen Polygon)
Geoprocessing (Intersect two polygon coverages)
Arcview Script (Create station point coverage)
DSS: Data storage format tool (C/C++)
Data format conversion from DSS file to TxRR input
file (C/C++)
Data format conversion from TxRR output file to DSS
file (C/C++)
DSPLAY: MS-DOS batch file & display control macro
(Continue)
Experience and Future Work
• DSS is efficient in time-series data storage. Data format conversion is not a big overhead.
• Display tools still need to be exploited.
• Avenue is not efficient in file reads/writes.
• An algorithm for combining historical data need to be developed.
– Data missing.