Rainfall Estimation at S-44 Site

Similar documents
Stream Discharge and the Water Budget

Water Management and Hydrology of Northeast Shark River Slough from 1940 to 2015

Evapotranspiration Estimation for South Florida

RAINFALL AVERAGES AND SELECTED EXTREMES FOR CENTRAL AND SOUTH FLORIDA. Thomas K. MacVicar

Technical Paper ERA #431

Chapter 5 CALIBRATION AND VERIFICATION

Lower Tuolumne River Accretion (La Grange to Modesto) Estimated daily flows ( ) for the Operations Model Don Pedro Project Relicensing

Jackson County 2014 Weather Data

Water Budget Analysis for Stormwater Treatment Area 2

REDWOOD VALLEY SUBAREA

Jackson County 2019 Weather Data 68 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center

Jackson County 2018 Weather Data 67 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center

Jackson County 2013 Weather Data

Coastal Flooding in Brevard County, Florida

StreamStats: Delivering Streamflow Information to the Public. By Kernell Ries

LOCATED IN INDIAN RIVER COUNTY PREPARED FOR S.J.R.W.M.D. AND F.W.C.D. DECEMBER, 2003 Updated 2007 Updated May 2014 PREPARED BY

Lake Tahoe Watershed Model. Lessons Learned through the Model Development Process

PRELIMINARY DRAFT FOR DISCUSSION PURPOSES

Water-budget Analysis for Stormwater Treatment Area 5

Rainfall Observations in the Loxahatchee River Watershed

INFLOW DESIGN FLOOD CONTROL SYSTEM PLAN 40 C.F.R. PART PLANT YATES ASH POND 2 (AP-2) GEORGIA POWER COMPANY

Estuarine Response in Northeastern Florida Bay to Major Hurricanes in 2005

Attachment B to Technical Memorandum No.2. Operations Plan of Ross Valley Detention Basins

MEMORANDUM FOR SWG

National Integrated Drought Information System. Southeast US Pilot for Apalachicola- Flint-Chattahoochee River Basin 20-March-2012

Adam Munson, Environmental Scientist III Resource Conservation and Development Department Southwest Florida Water Management District

Depth-Duration Frequency (DDF) and Depth-Area- Reduction Factors (DARF)

The Stochastic Event Flood Model Applied to Minidoka Dam on the Snake River, Idaho

Design Storms for Hydrologic Analysis

LITERATURE REVIEW. History. In 1888, the U.S. Signal Service installed the first automatic rain gage used to

Section 4: Model Development and Application

Comparing Spatial Distributions of Rainfall Derived from Rain Gages and Radar1. Abstract

Climate. Annual Temperature (Last 30 Years) January Temperature. July Temperature. Average Precipitation (Last 30 Years)

SEAGRASS COVERAGE TRENDS IN THE INDIAN RIVER LAGOON SYSTEM

Chapter 10 - Sacramento Method Examples

PENNSYLVANIA DEPARTMENT OF TRANSPORTATION ENGINEERING DISTRICT 3-0

Rucker Pond. Background

Great Lakes Update. Volume 194: 2015 Annual Summary

STORMWATER MANAGEMENT COMPUTATIONS. Mount Prospect

WATER MANAGEMENT REPORT FOR PAGE ESTATES

9 th INTECOL Orlando, Florida June 7, 2012

NIDIS Intermountain West Drought Early Warning System February 19, 2019

Illinois State Water Survey Division

Table (6): Annual precipitation amounts as recorded by stations X and Y. No. X Y

Technical Memorandum No RAINFALL

National Weather Service Flood Forecast Needs: Improved Rainfall Estimates

ARTICLE 5 (PART 2) DETENTION VOLUME EXAMPLE PROBLEMS

Continuing Education Course #101 Drainage Design with WinTR-55

HyMet Company. Streamflow and Energy Generation Forecasting Model Columbia River Basin

January 22, Coronado National Forest 300 West Congress Street Tucson, AZ Jim Upchurch, Forest Supervisor. Dear Mr.

3.0 TECHNICAL FEASIBILITY

Detailed Storm Rainfall Analysis for Hurricane Ivan Flooding in Georgia Using the Storm Precipitation Analysis System (SPAS) and NEXRAD Weather Radar

Groundwater Replenishment In The Coachella Valley, CA. WESTCAS 2018 Annual Conference June 21, 2018 Zoe Rodriguez del Rey, Water Resources

Tropical Storm Colin Briefing Last Briefing on this System

Table 1. August average temperatures and departures from normal ( F) for selected cities.

Impacts of precipitation interpolation on hydrologic modeling in data scarce regions

Presented by Jerry A. Gomez, P.E. National Hydropower Association Northeast Regional Meeting - September 17, 2009

2012 Rainfall, Runoff, Water Level & Temperature Beebe Lake Wright County, MN (# )

The following maps must be provided as a part of the ADA. The appropriate scale for each map should be determined at the pre application conference.

Sediment Trap. A temporary runoff containment area, which promotes sedimentation prior to discharge of the runoff through a stabilized spillway.

Storm Report : September 27, 2014

L-31N Seepage Management Field Test

Evapo-transpiration Losses Produced by Irrigation in the Snake River Basin, Idaho

120 ASSESMENT OF MULTISENSOR QUANTITATIVE PRECIPITATION ESTIMATION IN THE RUSSIAN RIVER BASIN

Monitoring Considerations and Costs

Flow estimations through spillways under submerged tidal conditions

E XTREME D ROUGHT An oppressive, long-term

Appendix D. Model Setup, Calibration, and Validation

Current Daily Simulated Subsurface Water Storage Conditions

Technical Note: Hydrology of the Lukanga Swamp, Zambia

73-2 have been satisfied; and

LOCAL CLIMATOLOGICAL DATA Monthly Summary November 2006

APPENDIX B HYDROLOGY

CLIMATOLOGICAL REPORT 2002

KANSAS GEOLOGICAL SURVEY Open File Report LAND SUBSIDENCE KIOWA COUNTY, KANSAS. May 2, 2007

Recurrence Intervals for the June 2006 Flood in Delaware and Otsego counties, New York

Near Real-Time Runoff Estimation Using Spatially Distributed Radar Rainfall Data. Jennifer Hadley 22 April 2003

Current Daily Simulated Subsurface Water Storage Conditions

LOCAL CLIMATOLOGICAL DATA Monthly Summary July 2013

National Integrated Drought Information System Southeast US Pilot for Apalachicola- Flint-Chattahoochee River Basin. 22 May 2012

DRAFT. REVISED Draft. Paso Robles Subbasin Groundwater Sustainability Plan Chapter 6

Monitoring Hurricane Rita Inland Storm Surge

Objectives: After completing this assignment, you should be able to:

January 2006 Climate Summary

The Climate of Payne County

Memo. I. Executive Summary. II. ALERT Data Source. III. General System-Wide Reporting Summary. Date: January 26, 2009 To: From: Subject:

LOCAL CLIMATOLOGICAL DATA Monthly Summary September 2016

Range Cattle Research and Education Center January CLIMATOLOGICAL REPORT 2016 Range Cattle Research and Education Center.

Storm Report: January 27, 2008 Maricopa County, AZ

Climatic Change Implications for Hydrologic Systems in the Sierra Nevada

Areal Reduction Factors for the Colorado Front Range and Analysis of the September 2013 Colorado Storm

PECKMAN RIVER BASIN, NEW JERSEY FLOOD RISK MANAGEMENT FEASIBILITY STUDY. Hydrology Appendix. New York District

MAPPING THE RAINFALL EVENT FOR STORMWATER QUALITY CONTROL

Speakers: NWS Buffalo Dan Kelly and Sarah Jamison, NERFC Jeane Wallace. NWS Flood Services for the Black River Basin

Shallow Karst Aquifer System of the Lake Belt Study Area, Miami-Dade County, Florida, USA EXTENDED ABSTRACT

9. PROBABLE MAXIMUM PRECIPITATION AND PROBABLE MAXIMUM FLOOD

NIDIS Intermountain West Drought Early Warning System September 4, 2018

Everglades National Park

The Climate of Bryan County

NIDIS Intermountain West Drought Early Warning System October 30, 2018

Transcription:

Technical Note EMA # 389 Rainfall Estimation at S-44 Site (January 2 "d, 3 rd, and 1 7 th, 1999 Events) March 1999 by Alaa Ali & Wossenu Abtew Hydro Information Systems and Assessment Department Environmental Monitoring and Assessment Division South Florida Water Management District 3301 Gun Club Road West Palm Beach, FL 33406

RAINFALL ESTIMATION At S-44 SITE (January 2"', 3 r d, and 17 th, 1999 events) Technical Notes by Alaa Ali and Wossenu Abtew INTRODUCTION The purpose of this communication is to reconstruct rainfall data at rain gage site S-44 (North Palm Beach) on the 2 " nd, the 3d, and the 1 7 t h of January of 1999 (unusually high rainfall events). The gage is believed to have malfunctioned on the 2" and 3 r d of January after recording a too high value, 32.53 inches. This value was revised later to 19.54 inches based on field comparison with a manual gage. Also, rainfall value recorded on the 17 h is believed to be too high (4.51 inches) compared to the surrounding gages and S-44 outflow. Flow, rainfall, and groundwater level data measured at nearby stations have been used to estimate the questionable rainfall data at S-44. The estimation is performed by two independent methods; statistical data analysis and water budget computation. The two methods show consistent results. This document is divided into four sections: 1) Brief description of C-17 Basin, 2) Available data used for the estimation, 3) Statistical data analysis, and 4) Water budget computation. S-44 STATION AND THE C-17 BASIN The C-17 basin is located in the northeastern part of Palm Beach County with an area of approximately 33 square miles (Figurel). The S-44 structure is located at Longitude and Latitude of 80 04' 54" 26 49' 00" respectively; and Easting and Northing of 955672, and 903634 feet respectively. Rainfall is the only source of water supply to this basin while C-17 is the only project canal. The C-17 canal and its only water control structure S-44 provide flood protection, drainage, and salt water intrusion prevention for the C-17 basin. Water flows Northward in the C-17 and is discharged to the Intracoastal Waterway through S-44 structure (Figure 1). For more information on C -17 basin, the reader is referred to the Eastern Palm Beach County Basin Atlas (Cooper and Lane, 1988). AVAILABLE DATA Data used for this study are daily discharge flow at S-44 structure and groundwater levels at nearby locations for the entire period of record. In addition, daily rainfall data at nearby stations including that at 5-44 structure for the months of January/1999 were selected for the analysis. Information about these data is presented in Table 1. Data Locations are depicted in Figure 1. The use of these data to estimate rainfall at S-44 site is presented in the remaining two sections,

Table 1. Information pertaining to the stations used for the estimation in this study. STATION AGCY TYPE UNITS STAT STRT END DBKEY LAT LONG X. feet Y, feet S44_R WMD RAIN Inches SUM 1991 1999 16674 264900 800454 955672 903634 S44_S WMD FLOW CFS MEAN 1985 1999 06795 264900 800454 955672 903634 PB-809 G USGS WELL Ft., NGVD MAX 1975 1999 02669 264124 800537 952104 857562 PB-561_G USGS WELL Ft., NGVD MAX 1973 1999 02694 264231 801204 916959 864092 PB-109_G USGS WELL Ft., NGVD MAX 1950 1992 02785 264842 801148 918173 901562 JUPITER R WMD RAIN Inches SUM 1976 1998 05888 265623 800603 949103 948322 PLANT IN R WPBC RAIN Inches SUM 1944 1999 05966 264254 800344 962287 866724 SIRG WMD RAIN Inches SUM 1994 1999 15730 265426 801130 919583 936308 C18W R WMD RAIN Inches SUM 1992 1999 16603 265219 801442 902277 923377 WPB ATRP_R WMD RAIN Inches SLIM 1991 1999 16610 264041 800635 946873 853183 S46 R WMD RAIN Inches SUM 1993 1999 16673 265603 800830 935812 946210 WPBFS_R WMD RAIN Inches SUM 1997 1999 GA832 264122 801105 922335 857199 Haverhill & WPB.W. RAIN Inches SUM 1999 1999 N/A 264424 800706 943963 875619 Earnest W.T.P

Figure I. C17 Basin and the nearby stations used for this analysis, 3

STATISTICAL ANALYSIS In this section, rainfall at S-44 is expressed in-terms-of: 1) Nearby rainfall data using the Reciprocal Square Distance Interpolation (RSDI), 2) Flow data at S-44 using correlation and regression analysis, and 3) Nearby Groundwater level data using correlation and regression analysis. The purpose of this exercise is to: 1) Investigate the applicability of each method in providing consistent rainfall estimation with the hydrologic conditions reported on these days; 2) Provide a useful check if any other source -Inf-, -a '. l a ); 3) Benefit the subsequent water budget computation. Rainfall estimation using neighbor stations. The average distance between S-44 and the nearest eight stations is about 9.3 miles with the nearet.station (PLANT IN) located -mi tojhe southeast. Given the nature of such a local rainfall storm i;-tnhesti _s are not near enough eo-paosid mealistic representation for this storm. Using the Reciprocal Square Distance Interpolation, RSDI, Method (Tabios and Sal-s,. 1985, Abtew et. al., 1993), and the nearest eight rainfall stations, the estimated rainfall on the " 2 d, the 3 rd, and 17 th of January of 1999 are: 4.6, 1.5, and 1.8 inches. The estimates on the 2 nd and 3rd are not consistent with other sources of information such as reported flooding, radar data, and flow discharge at S-44 structure. However, the Januaryll7 th estimate is consistent with that based on the Rainfall-Flow analysis. It was concluded that the January 2 nd and 3 rd events at S-44 can not be estimated using the surrounding rain gages. -- - -- Rainfall-Flow Correlation and Repression Correlation and linear regression analysis was conducted between S-44 daily rainfall (inches) and daily flow (cfs) data for several minimum rainfall "cut-off" values. Table 2 shows the results of this analysis. Rainfall data with minimum cut-off value of 1.0-inch shows the highest correlation (0.75). Table 3 shows the regression coefficients, the observed flow and the estimated rainfall on the 2 " d, 3rd, and 17'' of January of 1999. Table 2. S-44 Rainfall-Flow Correlation and Regression results. cut-off Correlation Lag Number of Regression (inches) (days) observations a b 0.5 0.724 0 296 0.25 0.00471 1.0 0.749 0 134 0.49 0.00506 1.5 0.749 0 65 0.70 0.00521 2.0 0.704 0 42 0.79 0.00509

Table 3. Observed flow and estimated rainfall at S-44 based on Rainfall-Flow Analysis. Date Flow Rainfall NOTES CFS) (inches) 01/02/99 1902.5 10.12 Rainfall (inches) = 0.49+0.00506*Flow (cfs) 01/03/99 1132.96 6.22 Regression coefficients are estimated based on I inch 01/17/99 267.23 1.85 minimum rainfall cut-off value, and 134 data points. Rainfall-Groundwater level Correlation Three groundwater level stations (PB-809 G, PB-561_G, and PB-109_G) were used for this analysis. The distance of these stations to S-44 are 8.75, 10.50, and 7.11 miles respectively. A Correlation analysis between a three-day moving sum of 5-44 rainfall and the corresponding water level change within this window shows that station PB-109_G is highly correlated with S- 44 rainfall data while the other two stations are poorly correlated. Table 4 presents the correlation and regression analysis results for "PB-109_G" for several minimum cut-off values of three-day rainfall. Table 4. Rainfall-Groundwater level Correlation and Regression results. cut-off Correlation Lag Number of Regression (inches) (days) observations a b 1.0 0.83 0 63 1.04 6.89 1.5 0.89 0 31 1.39 7.11 2.0 0,92 0 15 1.69 7.05 2.5 0.93 0 10 1.84 6.97 Table 4 indicates a robust correlation structure between water levels at station "PB- 109_G" and three-day rainfall sum at 5-44. Unfortunately, water level data are not available beyond May/1992 at this station. Therefore, a direct estimation of rainfall using the PB-109_G station is not possible. However, this rainfall-water level relationship is useful for the water budget computation. Based on 1-inch minimum rainfall cut-off value, this relationship is given as follows: where: Pt = 1.04 + 6.89* Aw, Pt= rainfall sum, in inches, in a three-day period up to "t" day. Aw, = Water level change, in feet, within the same period. WATER BUDGET ANALYSIS As mentioned earlier, rainfall is the only source of water supply to the C17 basin. Based on 5-44 daily flow data (Figure 2), it is noticed that the January 2 "d storm effect on the S-44 flow lasts up to the 15 th of January. Therefore, the water budget analysis was considered for the period between the 2 nd to the 15 h of January (14 days) within the C-17 basin. The water budget components are:

2000 1800 1600 1400 1200 1000 '- 800 600 400 200 0 Figure 2. S-44 Outflow during January. Days of January Rainfall Rainfall accumulated over the period of January 5L h to the 15d h was 0.71 inch. Rainfall accumulated over the budget period = rainfall of January (2, 3, and 4) + 0.71 Evapotranspiration (ET) = p4 + 0.71 Based on evapotranspiration study at the Everglades Nutrient Removal Project (Abtew, 1996), January daily ET is 0.1 inch. Therefore, the ET over the budget period is estimated as: S-44 outflow ET = 0.1*14= 1.4 inches. S-44 discharge volume = 12075 ac-ft., equivalent depth in inches = discharge volume/(tota] area in acre)*1 2 = 12075/(33*640)*12= 6.86 inches. Change in storage S = Awt * 12 * n, = (pt-1.04)/6.89 * 12*n, where: pt= rainfall sum in a three-day period up to "t" day.

8 = Change in subsurface storage in inches. ne = Effective porosity; dominant soil type is Basinger and Myakka fine sand. An average value for the effective porosity for sandy soils is 0.32 inch (Marsily, 1986). Water Budget Computation The general mass balance equation is: IN-OUT = Change in the storage. Where: IN = Rainfall depth accumulated during this period; OUT = Evapotranspiration, and equivalent depth due to S-44 outflow; Change in storage = Depth of water causing volume change in surface and subsurface storage. Given the above components, effective porosity of 0.32, and assuming no significant change in surface storage between the beginning and end of the water budget analysis period.; P4 +0.71 - (1.4 + 6.86 ) = S = (p4-1.04)/ 6.8 9 *12*ne 0.44 * p4= 6.97 p 4 = 15.84 inches. Since rainfall on January/4 th is 0; the rainfall sum for the 2 " d and the 3 rd of January is 15.84 inches. Based on the rain-flow computation, rainfall on the 2 nd and 3 rd is 10.13 and 6.23 inches respectively. Using the same proportions; rainfall, based on water level correlation, is 9.81 and 6.03 inches on the 2 nd; and 3' d respectively. CONCLUSION In this study, the estimation of questionable rainfall data at S-44 was carried out using statistical and water budget analyses. In the statistical data analysis, three sources of data were used (nearby rainfall data, S-44 flow data, and nearby groundwater level data). Estimation provided by the RSDT method using rainfall data from surrounding gages is inconsistent with the hydrologic conditions and radar data reported in that area on January 2 nd and 3 r. However, such an estimate on the 17th is consistent with that estimated by the rainfall-flow analysis. The rainfall-flow analysis and the water budget analysis provided consistent estimates, Using the available information and the results of these analyses, average estimated rainfall on January 2 nd, 3 ', and 17 h are 10, 6, and 1.8 inches respectively.

REFERENCES Abtew, W. Evapotranspiration Measurements and Modeling for Three Wetland Systems in South Florida. American Water Resources Association, Vol. 32, No. 3, June 1996. Abtew, W., J. Obeysekera, and G. Shih. 1993. Spatial analysis for monthly rainfall in South Florida. Water Resources Bulletin, 29(2): 179-188, 1993. Cooper, R. and J. Lane. 1988. An Atlas of Eastern Palm Beach County Surface Water Management Basins. Technical Memorandum, Water Resources Division, Resource Planning Department, South Florida Water Management District. Marsily, G. 1986. Groundwater Hydrology for Engineers. Harcourt Brace Jovanovich, Publishers, Academic Press, INC,, 440 p. Tabios III, G. and J. Salas. 1985. A comparative analysis of techniques for spatial interpolation of precipitation. Water Resources Bulletin, 21(3): 365-380.