University of Birjand-Research Group of Drought and Climate Change Journal of Drought and Climate change Research 3092-6076 3 4 2026 05 21 Estimation of Spatial-Temporal Variations of Water Quality Parameters Using Remote Sensing: A Case of Mindu Reservoir, Morogoro, Tanzania Estimation of Spatial-Temporal Variations of Water Quality Parameters Using Remote Sensing: A Case of Mindu Reservoir, Morogoro, Tanzania 45 72 3980 10.22077/jdcr.2025.9730.1155 FA Now Leonard Mwampamba Irrigation Engineering and Management, Sokoine University of Agriculture (SUA), Morogoro, Tanzania. 0009-0005-7131-3332 Fue Kadeghe Goodluck Senior Lecturer and Consultant in Mechatronics, Cybernetics and Precision Agriculture, Electronics and Precision Agriculture Lab (EPAL), Sokoine University of Agriculture, Morogoro, Tanzania Hieronimo Proches Department of Agricultural Engineering, School of Engineering and Technology, Sokoine University of Agriculture, Morogoro, Tanzania Mahoo Henry Department of Civil and Water Resources Engineering, School of Engineering and Technology, Sokoine University of Agriculture, Morogoro, Tanzania Journal Article 2025 07 12 Water quality assessment offers an evidence necessary for making sound decisions toward compliance of water to its designated use. This study used Remote sensing-based algorithms to assess spatial-temporal variations of water quality at Mindu Reservoir in the Morogoro Region for the period of six months from November-2024 to April-2025. Whereby, remotely sensed data were obtained through Sentinel-2 MSI sensor on a satellite temporal resolution basis, and the in-situ data were collected within the same period in the days coinciding and/or closely coinciding (±1 day) with Sentinel-2 satellite visit for better accuracy assessment. The assessed water quality parameters were Turbidity, Total Suspended Solids (TSS), Electrical Conductivity (EC), and potential of Hydrogen (pH). Various algorithms derived from literatures were used in the GEE JavaScript API for mapping water quality parameters (WQPs), and the Microsoft Excel was used to establish regression relationships between the remotely sensed indices and the in-situ measured values. The results show good accuracy and are statistically significant with R2 =0.7214, (p<0.00187); R2 =0.8046, (p<0.015); R2 =0.6838, (p<0.00317); and R2 =0.7394, (p<0.0014) observed in developed algorithms for Turbidity, TSS, EC, and pH estimation respectively. The RMSE and MAE were also used to assess the accuracy of generated algorithms in prediction of the actual in-situ measured data. Highlighting the potentiality of Remote Sensing in retrieving WQPs Water quality assessment offers an evidence necessary for making sound decisions toward compliance of water to its designated use. This study used Remote sensing-based algorithms to assess spatial-temporal variations of water quality at Mindu Reservoir in the Morogoro Region for the period of six months from November-2024 to April-2025. Whereby, remotely sensed data were obtained through Sentinel-2 MSI sensor on a satellite temporal resolution basis, and the in-situ data were collected within the same period in the days coinciding and/or closely coinciding (±1 day) with Sentinel-2 satellite visit for better accuracy assessment. The assessed water quality parameters were Turbidity, Total Suspended Solids (TSS), Electrical Conductivity (EC), and potential of Hydrogen (pH). Various algorithms derived from literatures were used in the GEE JavaScript API for mapping water quality parameters (WQPs), and the Microsoft Excel was used to establish regression relationships between the remotely sensed indices and the in-situ measured values. The results show good accuracy and are statistically significant with R2 =0.7214, (p<0.00187); R2 =0.8046, (p<0.015); R2 =0.6838, (p<0.00317); and R2 =0.7394, (p<0.0014) observed in developed algorithms for Turbidity, TSS, EC, and pH estimation respectively. The RMSE and MAE were also used to assess the accuracy of generated algorithms in prediction of the actual in-situ measured data. Highlighting the potentiality of Remote Sensing in retrieving WQPs https://jdcr.birjand.ac.ir/article_3980_9425be43ba92c2b4454ca7bf602efad8.pdf