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Evaluation of the effects of land-use change and increasing deforestation in the Sapanca Basin on total suspended solids (TSS) movement with predictive models

Temiz Temel, Sonmez Osman, Dogan Emrah, Oner Adnan, Opan Mücahit

Acta Geophysica

2022

Vol. 70, no 3

1331--1347

Sapanca Lake is a tectonically sourced freshwater resource and one of the rare natural water resources used as a source of drinking water. This study examined the change of land use and lake area in the natural water source basin subjected to human pressure for years. Landsat 5 TM (1987) and Landsat 8 TM (2010) satellite images were used. Satellite images were analyzed using ArcGIS 10.1 software. As a result of the analysis, it was observed that the natural vegetation was significantly destroyed between 1987 and 2010. Besides, the bathymetry maps of Lake Sapanca belonging to the years 1990 and 2010 were also examined, and accordingly, it was determined that there was a 2% reduction in the lake surface area. The decrease in the volume of the lake was thought to be due to sedimentation movement caused by land-use change, and the total amount of suspended solids, grain size, discharge, and temperature measurements were made between 2012 and 2014 in 12 streams which are sources of Sapanca Lake. Sediment prediction models have been developed under two different scenarios using measurement data from side streams. Artificial neural networks (ANN), Sediment rating curve, and multiple linear regression models were examined within the scenario models, and comparisons were made between the models. It was determined that ANN achieved the closest results with the measurement data.

Development of a relationship between hydrometric and hydrographic observations to predict reservoir capacity loss

Jabbar Y. C., Yadav S. M.

Acta Geophysica

2019

Vol. 67, no. 5

1451--1469

Accuracy of reservoir capacity loss estimation on daily timescale is dependent on the certainty of sediment load prediction, density estimate and capacity observed by consecutive hydrographic surveys. Data-scarce and uncertain data conditions restrict the development of a relationship between hydrographic surveys and hydrometric observations. The present study has been carried for Ukai Reservoir, India. A novel sediment rating curve ftting approach by optimization technique has been proposed in order to accurately predict sediment load from low-frequency sampled discharge and sediment concentration observations. The study demonstrates the validation of the bulk density estimate using statistical hypothesis testing and identifes the correctness of the hydrographic survey results. Application of the developed hydrometric and hydrographic relationship indicated that about 50% of the capacity loss of a year might occur during a single extreme event. The proposed approach can serve as a decision support system to monitor and manage sedimentation for the reservoir having uncertain data conditions.