**5.1. Daily spatial rainfall**

Gridded rainfall data generated daily over India at a grid resolution of 0.25° × 0.25° of measured rainfall from the large number of rain-gauge stations distributed over India are interpolated using IDW interpolation at 0.25° × 0.25°, and the spatial district rainfall is generated using GIS software. The daily spatial rainfall maps are given in **Figure 4**.

#### **5.2. Realised and forecast soil moisture on a pan India mode**

The daily soil moisture (**Figure 5**) has been computed by soil water balance (SWB) based on the method given in Ref. [6]. The spatial district rainfall values extracted in GIS are used as data source to generate the daily realised soil moisture using SWB model. Soil moisture generated from SWB model is further interpolated using Gaussian interpolation technique under Krigging to generate spatial soil moisture maps. In addition to daily soil moisture data, the cumulative difference between two consecutive days for soil moisture is also made using GIS software. Dynamic potential evapotranspiration (PET) computed from Indian Geostationary Satellite (INSAT 3D) interpolated in GIS is used in this model.

Soil moisture forecast (**Figure 6**) is made based on the quantitative rainfall forecast (NWP model output of T 1534). NWP model output (rainfall) values added by different Regional Meteorological Centres/Meteorological Centres of India on every Tuesday and Friday are

Multi-purposeful Application of Geospatial Data http://dx.doi.org/10.5772/intechopen.74217 199

being used as district level rainfall in SWB model to generate soil moisture forecast.

**Figure 3.** Spatial spread of daily, weekly, monthly and seasonal weather parameters over India.

• study of interpolation techniques to be used,

The digital data are being collected from different authorised agencies through IMD for the preparation of digital database. The mechanism for the preparation of agromet products is

In the context to the Indian agriculture, advisories have been given to farmers using weather information at the district level. Weather information and their departure from normal value at different temporal and spatial scales are useful for the preparation of agromet advisories. In view of that, daily, weekly, fortnightly, monthly and seasonal contours (**Figure 3**) are being generated utilising the realised weather observations for the parameter temperature (maximum temperature, minimum temperature and diurnal temperature variation), maximum and minimum relative humidity, cloud and wind speed. Synoptic observatory data received through Global Telecommunication System (GTS) are used to generate contours on a pan India mode. Weather information and their departure from normal value at different temporal and spatial scale is useful information for preparation of agromet advisories. In view of that daily, weekly, fortnightly, monthly and seasonal contours are being generated utilising the realised weather observations for the parameters temperature (maximum temperature, minimum temperature diurnal temperature variation), maximum and minimum relative humidity, cloud and wind speed. Synoptic observatory data received in GTS is used to generate contours on pan India mode. Using GIS software, the data are converted to spatial spread.

Gridded rainfall data generated daily over India at a grid resolution of 0.25° × 0.25° of measured rainfall from the large number of rain-gauge stations distributed over India are interpolated using IDW interpolation at 0.25° × 0.25°, and the spatial district rainfall is generated

The daily soil moisture (**Figure 5**) has been computed by soil water balance (SWB) based on the method given in Ref. [6]. The spatial district rainfall values extracted in GIS are used as data source to generate the daily realised soil moisture using SWB model. Soil moisture generated from SWB model is further interpolated using Gaussian interpolation technique under Krigging to generate spatial soil moisture maps. In addition to daily soil moisture data, the cumulative difference between two consecutive days for soil moisture is also made using GIS software. Dynamic potential evapotranspiration (PET) computed from Indian Geostationary

using GIS software. The daily spatial rainfall maps are given in **Figure 4**.

**5.2. Realised and forecast soil moisture on a pan India mode**

Satellite (INSAT 3D) interpolated in GIS is used in this model.

**5. Product generations from the ground observations using GIS**

• study of algorithm for agromet advisory.

198 Multi-purposeful Application of Geospatial Data

given in **Figure 2**.

**5.1. Daily spatial rainfall**

**Figure 3.** Spatial spread of daily, weekly, monthly and seasonal weather parameters over India.

Soil moisture forecast (**Figure 6**) is made based on the quantitative rainfall forecast (NWP model output of T 1534). NWP model output (rainfall) values added by different Regional Meteorological Centres/Meteorological Centres of India on every Tuesday and Friday are being used as district level rainfall in SWB model to generate soil moisture forecast.

**Figure 4.** Daily spatial rainfall.

**Figure 5.** Realised soil moisture on a pan India mode.
