Delineation and Mapping of Ground Water Quality in Kanchipuram District of Tamil Nadu Using GIS Techniques

Agriculture relies heavily on irrigation especially with groundwater which is a significant source in many countries. However, excessive use of groundwater can lead to a decrease in groundwater levels and cause scarcity of water. Irrigation requires good-quality water which is governed by dissolved ions. The groundwater quality is greatly influenced by global population growth, climate change and human activities including mining, agriculture, industrial effluents, seawater intrusion, household usage, etc., A study was conducted to evaluate the quality of groundwater for agriculture in various blocks of Kanchipuram district in Tamil Nadu. The sampling was done during March 2023 and about one hundred and fifty groundwater samples were collected from different blocks of the Kanchipuram district viz., Sriperumbudur(32 Nos), Kundrathur (28 Nos), Walajabad (34 Nos), Uthiramerur (29 Nos) and Kanchipuram (27 Nos). The physio-chemical (pH and EC) and chemical characteristics of the groundwater samples, including the cations Ca2+, Mg2+, Na+, and K+, as well as the anions CO32-, HCO3-, Cl-, and SO42-, were analyzed and the resulting properties were computed (SAR and RSC). The pH and EC values ranged from 3.29 to 8.49 and 0.09 to 5.22 dS m-1, respectively. The Residual Sodium Carbonate (RSC) ranged from nil to 32 meq L-1, while the Sodium Adsorption Ratio (SAR) ranged from 0.19 to 34.78 mmol L-1. According to the CSSRI, Karnal Water Quality Classification about 38 percent of the samples falls in the good quality category, alkali water was about 57.33 percent and Saline water was 4.67 percent in Kanchipuram district. The Good quality water was dominant in Uthiramerur block followed by the Sriperumbudur block. The Saline and Alkali water was dominant in Sriperumbudur and Kanchipuram blocks respectively.

Assessing Land Use Dynamics of Lower Bhavani Basin Using Multiple GIS Platforms

Land use describes the actual form of land, such as a forest or open water and classification based on human utilization. Land use map provides the information about the current landscape of an area. In this study, the Lower Bhavani basin's land use and land cover were classified using GIS platforms and data from the Landsat 8 satellite. The platform utilized in this study were Semi-Automated Plugin (SAP) in QGIS and Random forest method in Google Earth Engine (GEE). The findings suggested that both platforms performed efficiently and displayed comparable percentages of land covered by various land use features. The accuracy of the resulting land use map was evaluated using a Google Earth image, and it was discovered that SAP and GEE hold 91.8% and 92.6% of the total accuracy. This study aids in evaluating and classifying the various Geographic Information System platforms land use trends.