Some area in Indonesia every year suffered from drought, this situation become worst when the impact not only to the natural environment but also the socio-economic condition. Most of them are farmer who worries about water supply in their field.
Number of farmers household in Indonesia is more than 26,000, based on the statistical report of BPS (Indonesian Statistical Agency) year 2013. They are mostly rely on agricultural activity, and they fields rely on irrigation to provide water for crops.
Especially on June-October, generally speaking, this period is dry season in Indonesia. While during January-February, a corresponding low pressure system over Asia causes the pattern to reverse. The result is a monsoon which is augmented by humid breezes from the Indian Ocean, producing significant amounts of rain throughout many parts of the country.
Monsoon will produce high amount of precipitation, this could lead to flood in some places, but could bring much advantage if we can manage the situation. Indonesia have many dam and irrigation system, but the monitoring of actual condition and the management of the infrastructure is lack. This situation lead to worst condition during dry season, when the number of precipitation is very low.
Remote sensing evaluated as the effective. and efficient method to monitor periodically the land use changes/cover surrounding the dam and irrigation environment. To catch and harvest huge amount of water during monsoon the dam condition need to be healthy (no sedimentation, land cover changes, etc). The changes of the area of the dam will be affected the amount of water could be harvested.
I provide one example of the changes of dam environment in Cianjur, West Java. In this analysis I employed NDWI (Normal Difference Water Index) for Landsat 7 ETM+ year 2003 and Landsat 8 OLI year 2013.
NDWI is expressed using the following equation:
NDWI = (NIR – SWIR)/(NIR+SWIR),
where NIR is the reflectance or radiance in a near infra-red wavelength channel (0.760 – 0.900 μm), and SWIR is the reflectance or radiance in a short wave infrared wave-length channel (1.550 – 1.750 μm). NIR and SWIR correspond to bands 4 and 5 for ETM+ images, respectively. While for OLI images, NIR and SWIR correspond to band 5 (NIR, 0.845 – 0.885 μm) and band 6 (SWIR, 1.560 – 1.660 μm).
The result shown in the following figure
We can see there is the large changes of dam environment during 10 years. Red colors represented for water in year 2003, while blue color for water in year 2013. The area of dam in year 2003, was ~5,700 ha, but dramatically decreased to ~4,400 ha in year 2013. Or in other word, its lost ~1,300 ha during ten years.
This kind of remote sensing analysis could be employ in many area in Indonesia, furthermore I would like to propose some “time-line” management to overcome drought as shown in the following figure:
During January to March is time for catch and harvesting water, April-May is for preparing the infrastructure to supply the water, June to September is period to supplying water to the suffered area, and October-December is time for manage the physical environment of the dam. Monitoring of land use land cover can be done in the whole year.
Hope any person in charge in Indonesia would try to understand this simple idea.