Analysis of accuracy comparison tidal global (FES2014, TPXO9) and regional (BIG Prediction) models to the existing tides in Surabaya and surrounding waters

Tidal data has a significant role in various fields in hydrographic surveys and navigation, port planning, and other coastal management. The number of fixed tide stations in Indonesia is minimal compared to the vast territorial waters in Indonesia. So that for areas that are not covered by tidal fixed stations, direct tidal observation with a certain length of observation is necessary, and of course, this requires quite expensive costs. Fortunately, there are regional and global tidal data predictions that can be used to determine tidal conditions in Indonesian waters. In this study, the regional (BIG) and the global (FES2014 and TPXO9) tidal data prediction models were validated with direct observation in the five locations such as Surabaya, Gresik1, Gresik2, Bangkalan, and Giligenting for 39 hours. The root means square error (rmse) calculation results show that in the five locations, the BIG tidal prediction has the smallest rmse value in three tidal stations at Gresik 1, Gresik 2, and Gili Genting with 0.303 m, 0.050 m, and 0.155 m respectively. At the same time, the TPXO9 tidal model shows the biggest rmse at Gresik 1, Gresik 2, and Bangkalan with 0.420 m, 0.195 m, and 0.630 m, respectively.

A holistic approach towards a more sustainable urban and port planning in tourist cities

Purpose This contribution aims to demonstrate that the adoption of a holistic approach to the development of infrastructures supporting the growth of cruise tourism can represent a trigger for a more sustainable urban and port planning in the Moroccan context. Although, along with this growth, there are global-local issues pertaining to sustainability and resilience that need to be addressed to support sustainable urban and social development of tourist cities. Design/methodology/approach Documents and literature review were used to develop an in-depth analysis related to the different fields involved in the proposed theoretical reflection. Scientific publications, data and international statistical reports have been used to validate the approach. Findings The work provides empirical insights to show the strengths of the country related to the sustainability, suggesting that they deserve to be integrated, involving urban planning, green energy transition, as well as the economic and social sustainability of tourism industry. Originality/value This paper aims to stimulate a debate among stakeholders and scholars involved on tourist port cities urban planning to avoid a “silos” approach and to favour a more sustainable infrastructure development process. In that sense, the paper fulfils the need to provide a basis to encourage the integration of different strategic topics and agenda concerning social and economic growth of tourist port cities.

Short Term Forecast of Container Throughput: New Variables Application for the Port of Douala

An accurate container throughput forecast is vital for any port. Since overall improvements in port performance and competitiveness can be derailed by port bottlenecks, ports need to find leverage to identify and prioritize measures to improve weak key performance indicators (KPIs) to attain growth opportunities. Prior studies had modeled container throughput from socio-economic and growth projection factors. This study aims to provide a practical method for forecasting the optimal container throughput a port can physically handle/attract given a certain level of terminal operation efficiency through random forest (RF) and multilayer perceptron (MLP) models. The study variables are derived from the port operations dimension and include ship turnaround time, vessel draft, container dwell time, berth productivity, container storage capacity, and custom declaration time. Evaluations are made based on the R-squared, NRMSE, MAE and MAPE. Model comparison is deduced with seven competing models in container throughput forecasting. The findings indicate that the RF model is a potential candidate for forecasting the engineering optimal throughput of Douala port. Model interpretation is provided through feature importance and partial dependence plots. The findings from this study will help reduce uncertainty and provide leverage for port management to spot bottlenecks and engage in better port planning and development projects which will strengthen their international competitive advantage.