Seismic Network Operations

IU KOWA

Kowa, Mali

IU KOWA commences operations on: 1998,067

Country Flag
Host: National Center for Science and Technology Research
Latitude: 14.497
Longitude: -4.014
Elevation: 321
Datalogger: Q330
Broadband: STS-2_High-gain
Accelerometer: FBA_ES-T_EpiSensor_Accelerometer
Telemetry Status at the NEIC: Last Data In Less Than 10 Minutes
Station Photo Station Photo Station Photo Station Photo Station Photo Station Photo 

Site Description: Located in the Niger River delta region of the Sahara desert in Mali continent of Africa. KOWA operates as a remote IRIS2 station with the data processor operating at the airport in Sevare and the acquisition unit operating at the Dogon village of Kowa approximately 10k from Sevare. The site uses radio modems for data transmission and solar power. A dialup modem is operational. Internet access is not available at this time. National language is French with 75% of the poulation speaking Bambara.

Vault Condition: 40 meter horizontal tunnel with approx. 10-15 meters of overburden. (solid rock), *Dry and very hot

Site Geology: Sandstone

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
20LN2Kinemetrics FBA ES-T EpiSensor AccelerometerCG1.000.0090.005.00
20HN2Kinemetrics FBA ES-T EpiSensor AccelerometerTG100.000.0090.005.00
10VH2Trillium 240 broad bandCG0.100.0090.005.00
10LH2Trillium 240 broad bandCG1.000.0090.005.00
10HH2Trillium 240 broad bandTG100.000.0090.005.00
10BH2Trillium 240 broad bandCG40.000.0090.005.00
00VH2Streckeisen STS-2 High-gainCG0.100.0090.005.00
00LH2Streckeisen STS-2 High-gainCG1.000.0090.005.00
00HH2Streckeisen STS-2 High-gainTG100.000.0090.005.00
00BH2Streckeisen STS-2 High-gainCG40.000.0090.005.00
31LDOCI/PAS pressure sensorCW1.000.000.000.00
30LDOlower quality chip sensor in Setra boxCW1.000.000.005.00
20LNZKinemetrics FBA ES-T EpiSensor AccelerometerCG1.00-90.000.005.00
20LN1Kinemetrics FBA ES-T EpiSensor AccelerometerCG1.000.000.005.00
20HNZKinemetrics FBA ES-T EpiSensor AccelerometerTG100.00-90.000.005.00
20HN1Kinemetrics FBA ES-T EpiSensor AccelerometerTG100.000.000.005.00
10VH1Trillium 240 broad bandCG0.100.000.005.00
10VMWTrillium 240 broad bandCH0.100.000.000.00
10VMVTrillium 240 broad bandCH0.100.000.000.00
10VMUTrillium 240 broad bandCH0.100.000.000.00
10VHZTrillium 240 broad bandCG0.10-90.000.005.00
10LHZTrillium 240 broad bandCG1.00-90.000.005.00
10LH1Trillium 240 broad bandCG1.000.000.005.00
10HHZTrillium 240 broad bandTG100.00-90.000.005.00
10HH1Trillium 240 broad bandTG100.000.000.005.00
10BHZTrillium 240 broad bandCG40.00-90.000.005.00
10BH1Trillium 240 broad bandCG40.000.000.005.00
00VHZStreckeisen STS-2 High-gainCG0.10-90.000.005.00
00VH1Streckeisen STS-2 High-gainCG0.100.000.005.00
00LHZStreckeisen STS-2 High-gainCG1.00-90.000.005.00
00LH1Streckeisen STS-2 High-gainCG1.000.000.005.00
00HHZStreckeisen STS-2 High-gainTG100.00-90.000.005.00
00HH1Streckeisen STS-2 High-gainTG100.000.000.005.00
00BHZStreckeisen STS-2 High-gainCG40.00-90.000.005.00
00BH1Streckeisen STS-2 High-gainCG40.000.000.005.00
Heliplot
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Latency
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Availability, Year
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Availability, Since 1972
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Availability, 2 Month
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As part of the annual calibration process, the USGS runs a sequence that includes a random, a step, and several sine wave calibrations.  The USGS analyzes the random binary calibration signal in order to estimate the instrument response.  The figures below show the results from the analysis of the most recent processed calibration at the station.

We use an iterative three-step method to estimate instrument response parameters (poles, zeros, sensitivity and gain) and their associated errors using random calibration signals. First, we solve a coarse non-linear inverse problem using a least squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a non-linear parameter estimation problem to obtain the least squares best-fit Laplace pole/zero/gain model. Third, by applying the central limit theorem we estimate the errors in this pole/zero model by solving the inverse problem at each frequency in a 2/3rds-octave band centered at each best-fit pole/zero frequency. This procedure yields error estimates of the 99% confidence interval.

LocChanCal DateEpoch-SpanGradeAmp Nominal Error (dB)Amp Best Fit Error (dB)Phase Nominal Error (degree)Phase Best Fit Error (degree)SensorCal Type
00BHZ2011:148 2011:147 to No Ending TA0.0138270.0122690.070480.076279 STS-2-HGRandom
10BHZ2011:149 2011:147 to No Ending TA0.014360.00769990.104320.088975 TR240Random
  1. Current Issues
    Since Aug. 12 (2012) timing quality has been bad. Telemetry has stopped possibly due to power problems.
  2. 2011-11-05
    Power system repaired and data flow has resumed.
  3. 2011-06-11
    Data flow stopped due to power system failure.
  4. 2011-05-25
    Upgraded to Q330 digitizer.