OVERVIEW OF IMPROVED USE OF RS INDICATORS AT INAM. Domingos Mosquito Patricio

Transcription

1 OVERVIEW OF IMPROVED USE OF RS INDICATORS AT INAM Domingos Mosquito Patricio

2 Introduction to Mozambique /INAM Introduction to AGRICAB/SPIRITS Objectives Material & Methods Results & discussion Conclusions

3 Mozambique is located in: tropics and subtropics of southern Africa: -between latitudes 10º27 e 26º52 South and Longitudes 30º12 e 40º51 East Surf: km² (Land= km² and interior waters= km² ) Coast line: km Pop: Inhab (Projection in 2012)

4 Climate: Tropical Two Seasons -Rainy and hot: from October to April -Winter and dry: from May to September Annual rainfall: mm (Centre and north); mm (South) Average air temperature: 25ºC-27ºC (summer) and 20ºC-23ºC (winter) Extreme Events -Tropical cyclones -Floods -Drought

5 Example of El Niño (warm) and La Niña (cool) events in the tropical pacific, related to drought and floods, respectively, in Southern Africa Source: Weak with 0.5 to 0.9 SST anomaly; Moderate (1 to 1.4) and Strong ( 1.5)

6 INAM is a government institution responsible for coordinating the meteorological activities at national level in all domains, namely, of observation, dissemination and application of meteorology, with emphasis for: Climatology Agrometeorology Aviation, Marine Meteorology Air Quality Monitoring Renewable energy

7 Meteorological Stations Network 36 synoptic stations (24 classical and 12 AWS); 13 agroclimatological stations; 42 climatological stations; and 2 weather radars. The density of stations of our network is low, sparse and non representative having locations without any station.

8 AGRICAB - Is a framework for enhancing Earth Observation (EO) capacity for Agriculture and Forest Management in Africa as a contribution to GEOSS. SPIRITS Software designed for the analysis of large time series of EO data, for assisting in the creation of maps and graphs, extracting historical statistics and calculating anomalies.

9 Evaluate the start and the end of the season using RFE and NDVI. Evaluate the impact of rainfall on vegetation/crops. Verify the magnitude of RFE and NDVI in the years when the extreme events were observed.

10 SPIRITS Software was used for images analysis, processing and quick look generation. Ten day time series of actual RFE and NDVI images were used In the anomalies, the following equations were used for: Relative Difference Where: X=actual; Standardized Difference y=year; p=period in the year (dekad). For convergence of evidence the observed data also were used, where possible.

11 GAZA, SOFALA & TETE PROVINCES

12 The ten day time series of RFE from show that in general the rainy season goes from October to March-April, varying from location to location in the study area. The ten day time series of NDVI from show that the vegetation reacts to rainfall occurrence later and the peak of rainfall usually follows the peak of rainfall. The definition of the shift in the start of the growing season becomes very valuable using SPIRITS Software. The growing season concept shows that this period in normal conditions varies from Nov-Jul in Xai-Xai, Nov-Jun in Beira and Jan-Mar in Tete.

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15 Growing season shift concept for the Xai-Xai, Beira and Tete stations

16 Growing season concept for the Xai-Xai, Beira and Tete stations Rain, PET (mm) Growing season for Xai- Xai Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Rain (mm) PET/2 Rain, PET (mm) Growing season for Beira Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Rain (mm) PET/2 200 Growing season for Tete Rain, PET (mm) Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Rain (mm) PET/2

17 The vegetation is affected not only by the drought but also by floods. Our results show that RFE in Gaza was above normal in 1999/00 and the vegetation fluctuated along the normal line. In 2000/01, the vegetation was more affected by intensive rains or floods, mainly in Sofala and Tete. During the year of low rainfall (2002/03 season), the vegetation fluctuated along the normal line (up and down).

18 In Gaza in 1999/00 the RFE was above normal and the vegetation fluctuated along the normal line. In 2000/01 and 2002/03 the figure shows the RFE below normal and the vegetation fluctuated along the normal line Xai- Xai Obs rainfall (mm) Oct1 Nov1 Dez1 Jan1 Feb1 Mar1 Apr1 May1 Jun1 Jul1 Aug1 Sep1 99/00 00/01 02/03 Avg

19 In Sofala in 1999/00 and 2000/01, the RFE was above normal but the vegetation was negatively affected with emphasis for 2000/01. In 2002/03 the RFE sometimes was below normal influencing the vegetation performance Beira Obs rainfall (mm) /00 00/01 02/03 Avg Oct1 Nov1 Dez1 Jan1 Feb1 Mar1 Apr1 May1 Jun1 Jul1 Aug1 Sep1

20 In Tete in 1999/00 and 2002/03, the RFE was below normal influencing the vegetation performance. In 2000/01 the vegetation was negatively affected by intense rains (floods) Tete Obs rainfall (mm) Oct1 Nov2 Dez3 Feb1 Mar2 Apr3 Jun1 Jul2 Aug3 99/00 00/01 02/03 Avg

21 It was verified that in 1999/00 and 2000/01 when intense rainfall (floods) was registered, the vegetation didn't perform well mainly in Sofala and Tete provinces. However, in 2002/03 season, the vegetation was also influenced negatively by rainfall deficit but with low magnitude.

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23 The results show that the vegetation is affected not only by the drought but also by floods due to water logging. Due to the fact that the meteorological stations network is sparse and not representative to be used for spatially rainfall monitoring focusing to the agriculture sector in terms of onset and end of rainy season, the satellite remote sensing products (RFE and NDVI) apart from low spatial resolution can be a better alternative for monitoring vegetation/crop growing cycle, using SPIRITS - very valid software for time series analysis. The quick looks and graphs of RFE vs NDVI time series images combined with ENSO information were used to detect anomalous situations.

24 The similarity in SPIRITS is an alternative approach to define the shift in the start of the growing season. The EO data/products can help INAM to improve its operational activities (e.g. bulletins, seasonal forecast evaluation, solar radiation processing, ET, posters, flyers preparation, etc.).

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