Shashi Ekanayake

GIS-based irrigation and water management represents a key technology in modern agriculture, as it enables efficient planning and use of water while minimizing losses. However, challenges related to data accuracy and reliability are significant and cannot be overlooked. The integration of data from various sources, such as remote sensing, hydrological models, and field measurements, often leads to potential inconsistencies that can affect the quality of decision-making.

1. Data Inconsistencies

Data from different sources often have varying spatial and temporal resolutions, which can lead to issues in the precision of modeling and interpretation of water resource conditions. For example, satellite data may have lower resolution compared to field measurements, which creates discrepancies in assessing the actual condition of land or water resources.

2. Sensor Errors

The sensor equipment used for data collection can have errors due to various factors such as adverse weather conditions, technological faults, or inaccurate calibration of devices. These errors can affect the accuracy of the data used for water resource management.

3. Lack of Ground-Truth Verification

One of the major issues in applying GIS in agriculture is the lack of adequate ground-truth verification. Remote sensing can provide useful information, but it is essential that this data is confirmed in the field to ensure its accuracy. Without this confirmation, decisions made based on unverified data can lead to poor agricultural practices and mismanagement of resources.

4. Necessary Improvements

To improve data accuracy, investment is needed in advanced technological methods for automatic data verification, as well as in the development of algorithms that can reduce discrepancies between different data sources. Additionally, better field measurements and their integration with remote sensing data can help minimize errors and improve the precision of forecasts.

Managing water resources with GIS technology has enormous potential, but challenges related to data accuracy must be addressed to enable precise and efficient management. Understanding and resolving these challenges through improved data collection, verification, and analysis methods is crucial for achieving sustainable water resource management in agriculture.

Just as the topography in agricultural areas can change over very short distances, soil horizons can also change over very short distances. In calculations made with remote sensing, it is very difficult to see these small changes, especially to capture changes in horizons.

These micro topography changes can prevent sensors from representing the land. Since it would be difficult and laborious to capture these changes by sampling the entire area, the irrigation method created with GIS should be calibrated in the field by checking GIS (surface wetness, plant development, etc.).

Since each agricultural land has its own characteristics and changes, field calibration is important in this regard.