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Natural and anthropogenic factors have caused changes in channel morphology that reflects the capacity of channels to carry floodwaters. Using spatio-temporal multispectral aerial imagery and topographic data, remote sensing plays an important role in assessing channel morphological changes. The Dry Creek channel in South Australia, has undergone channel modification due to urbanisation development. The objective of this study was to investigate the trends of channel morphological changes in Dry Creek over the last forty-three years (1979-2022). To extract the channel boundaries and morphological parameters, very high-resolution aerial imagery and a LiDAR-derived digital elevation model were processed using ArcGIS Pro. The analysis focused on patterns of the longitudinal profile, erosion and deposition within the selected reaches. The construction of Mawson Lakes Pond on the existing Dry Creek channel, as well as the construction of residential buildings resulted in channel planform changes in the downstream sections of Dry Creek. As a result, the channel centreline shifted to the southwest by a maximum of 478 m with an average of 217 m after 1998. These adjustments led to an increase in the sinuosity index from 1.08 to 1.22. The study also revealed net deposition depths of 3.4 cm and 3.6 cm between 2018 and 2022 at two different reaches, corresponding to the annual deposition volumes of 981 m3. Regular desilting is necessary to avoid a reduction in channel capacity and potential flooding in the surrounding environment. Furthermore, a significant vegetation growth has been observed, contributing to increased surface roughness and decreased channel bed slope, resulting in reduced channel carrying capacity. The study findings can be used as a baseline for future studies on channel morphology change and highlight the importance of implementing suitable measures such as de-silting to mitigate the silt deposition and remove unwanted vegetation during the dry season. Consequently, the management of Dry Creek can be improved to mitigate flooding risk and maintain optimal channel capacity. [ABSTRACT FROM AUTHOR]

Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling. [ABSTRACT FROM AUTHOR]