Environmental causes of navigation accidents in the Guaíba River waterway

Causas ambientais de acidentes de navegação na hidrovia do Rio Guaíba

ABSTRACT

This study analyzed the possible causes of accidents on the Guaíba River waterway between 2007 and 2023, using historical reports, numerical modeling, and assessments of critical meteorological and hydrodynamic conditions. Data on wind, visibility, water levels, and flow rates were examined both analytically and graphically. A numerical model simulated the river’s hydrodynamics, identifying key parameters affecting navigation safety. The analysis revealed that various environmental forces such as fog, currents, waves, and wind significantly contributed to accidents, often acting in combination. All recorded accidents were groundings, and the Pedras Brancas Channel as the most critical grounding hotspot along the waterway. Wind speeds above 7 m/s, current speeds above 0.5 m/s, water levels below 40 cm, and wave heights exceeding 20 cm form the set of critical values for navigation safety. These technical insights enable Port Authorities to enhance navigational safety through data-driven interpretations and operational decisions.

Keywords:
Grounding; Numerical modeling; Environmental variables; River hydrodynamics; Navigation safety; Environmental risk

RESUMO

Este estudo analisou as possíveis causas de acidentes na hidrovia do Rio Guaíba entre 2007 e 2023, utilizando relatórios históricos, modelagem numérica e análise de condições meteorológicas e hidrodinâmicas críticas. Dados sobre vento, visibilidade, níveis de água e vazões foram analisados ​​analítica e graficamente. Um modelo numérico simulou a hidrodinâmica do rio, identificando parâmetros críticos para a segurança da navegação. A análise revelou que diversas forças ambientais como neblina, correntes, ondas e vento contribuíram significativamente para os acidentes, muitas vezes atuando em combinação. Todos os acidentes registrados foram encalhes, e o Canal das Pedras Brancas foi o ponto crítico de encalhe ao longo da hidrovia. Velocidades de vento acima de 7 m/s, velocidades de corrente acima de 0,5 m/s, níveis de água abaixo de 40 cm e ondas acima de 20 cm formam o conjunto de valores críticos para a segurança da navegação. Esses insights técnicos permitem que as Autoridades Portuárias melhorem a segurança da navegação por meio de interpretações baseadas em dados e decisões operacionais.

Palavras-chave:
Encalhes; Modelagem numérica; Variáveis ​​ambientais; Hidrodinâmica fluvial; Segurança da navegação; Risco ambiental

INTRODUCTION

Ports are essential for economic growth and development, with 50% of global trade, in terms of value, carried out by maritime transport (Verschuur et al., 2022). Over the past decades, there has been an increase in global maritime transport, particularly in dry cargo, including bulk goods and containerized cargo, which account for nearly three-quarters of total freight (United Nations Conference on Trade and Development, 2022). The location of ports along rivers and in low-altitude coastal areas makes them exposed to the impacts of extreme weather and natural disasters (Verschuur et al., 2023). Therefore, proper management of ports and waterways plays a fundamental role in today’s global economy.

In Brazil, ports function as major logistical hubs in transport networks and exert significant influence on cities, stimulating economic and territorial development (Asmus et al., 2009). Waterway transport, in this context, is identified as the most efficient and cost-effective mode of transport (Instituto de Pesquisa Econômica Aplicada, 2014). The country has 18,616 km of economically navigable inland waterways (Agência Nacional de Transportes Aquaviários, 2019). However, its development depends on sophisticated transshipment facilities, primarily ports and terminals (Instituto de Pesquisa Econômica Aplicada, 2014).

Despite the critical importance of ports, there is a scarcity of specific studies on the safety of waterways and ports in Brazil, particularly in inland waters. This lack of available data and published studies is especially notable concerning navigation accidents.

Several studies have been conducted on the safety of port areas and adjacent waterways (Li et al., 2023; Antão et al., 2016; Zhang et al., 2016; Pak et al., 2015; Shu et al., 2013; Debnath & Chin, 2009; Bellsolà Olba et al., 2019). These studies, although addressing the same general topic, differ in spatial scale and approach. Antão et al. (2016) conducted an extensive assessment of Occupational Health and Safety Performance Indicators in 526 port areas worldwide. Pak et al. (2015) analyzed data collected from 21 captains with over 10 years of experience in ship operations, applied a fuzzy analytic hierarchy process, and identified the safest and riskiest ports among five ports in South Korea. Bellsolà Olba et al. (2019) proposed the Nautical Port Risk Index (NPRI), which allows any port to develop an indicator based on its characteristics. The application considered the Port of Rotterdam and enabled the creation of a risk map using the adopted approach.

Another topic closely related to the proper functioning of ports is navigation safety. The increase in maritime cargo transport and vessel size leads to higher vessel traffic in ports, raising potential navigation risks (Bellsolà Olba et al., 2019). Several studies have focused on collision and grounding accidents (Bye & Aalberg, 2018; Goerlandt et al., 2017; Graziano et al., 2016; Kum & Sahin, 2015; Macrae, 2009), while others have analyzed various types of accidents (Valdez Banda et al., 2015; Ventikos et al., 2017; Eliopoulou et al., 2016; Antão & Soares, 2019).

Some studies indicate an increase in the frequency of ship accidents in the post-2000 period (Panagiotidis et al., 2021; Eliopoulou et al., 2016; Ventikos et al., 2014). This increase has been attributed to traffic growth during a period of global economic expansion and improvements in the reporting practices of such incidents (Eliopoulou et al., 2016). However, underreporting is a frequently raised issue in the literature (Bye & Aalberg, 2018; Eliopoulou et al., 2016; Hassel et al., 2011; Psarros et al., 2010), in addition to data scarcity and quality being fundamental problems in the statistical analysis of historical ship accident records (Eliopoulou et al., 2016).

Regarding accidents, studies aim to identify types and causes. Macrae (2009) analyzed accident and collision reports and found common patterns: groundings resulted from a failure to properly plan a navigation passage, while collisions often stemmed from difficulties in identifying the presence or speed of another vessel. Other studies attempt to identify patterns in incidents, vessel types, and vessel ages (Eliopoulou et al., 2016, 2023; Rawson et al., 2021). According to Eliopoulou et al. (2016), fishing vessels and passenger ships do not appear to be related to the age of occurrence. Vehicle carriers and bulk carriers show an increased frequency of accidents in vessels over 20 years old. “Roll-on, Roll-off” (RoRo) cargo ships exhibit significantly high frequencies in the age group of less than five years.

The contribution of human factors to maritime accidents is also a common topic in the literature (Dominguez-Péry et al., 2021; Coraddu et al., 2020; Cordon et al., 2017; Graziano et al., 2016; Chauvin et al., 2013; Celik & Cebi, 2009; Hetherington et al., 2006). According to Graziano et al. (2016), most user failures fall into the category of navigation task errors (28.7%), which are strongly related to vessel maneuvering when entering or leaving a port/canal.

Finally, studies focusing on meteorological and oceanographic conditions and their probability or occurrence in accidents are also found (Rawson et al., 2021; Panahi et al., 2020; Antão & Soares, 2019; Rezaee et al., 2016; Heij & Knapp, 2015; Wu et al., 2009). Rezaee et al. (2016) investigated the effects of adverse weather conditions (low air temperature, presence of ice, strong winds, and high-pressure Laplacian) on commercial fishing activities and vessel incidents in the Canadian Atlantic. Panahi et al. (2020) developed a model based on a Bayesian Belief Network (BBN) to assess Extreme Weather Events in the Arctic. Rawson et al. (2021) applied a machine learning technique to monitor an incident during the U.S. Atlantic hurricane season.

According to Bye & Aalberg (2018), the past two decades have provided significant insights into ship accidents, allowing them to be classified into four main categories: external or environmental conditions, vessel conditions, human conditions, and organizational conditions. In Brazil, some studies (Zappes et al., 2013; Saito et al., 2015; Fontes et al., 2023) have been conducted on Brazilian waterways and ports, particularly in the Amazon waterways.

Studies such as Zappes et al. (2013) analyzed accidents between cetaceans and fishing vessels in the Central Amazon, proposing mitigation measures to reduce accident occurrences. Additionally, Fontes et al. (2023) investigated the main challenges faced by passenger ships in the Amazon, proposing an integrated framework for accident prevention and discussing the social relevance of the suggested measures.

Besides these studies, Saito et al. (2015) analyzed historical accident data from the Tietê-Paraná Waterway between 2003 and 2012, revealing a relatively low number of accidents but a high proportion of fatalities. The study highlighted the significant influence of human and climatic factors and suggested that future research should consider the impact of human error and situational variables to better understand and mitigate accidents in the region.

Despite this, few studies focus on navigation safety in Brazilian waterways and ports. In some cases, data are scarce, unavailable, or even nonexistent. For the Guaíba Waterway, only news reports are found.

In this context, this study aims to conduct a detailed investigation of accidents based on historical reports from 2007 to 2023, evaluate the occurrences, and relate them to known environmental factors in the Guaíba River and the delta of the Jacuí Waterway, located in southern Brazil.

MATERIAL AND METHODS

Study area

The study was conducted in the Guaíba River waterway (an area of 496 km²) and the surroundings of the Jacuí Delta, located in the state of Rio Grande do Sul (RS), the southernmost state of Brazil. These environments are formed by the confluence of the Jacuí, Sinos, Caí, and Gravataí rivers, receiving drainage from nine sub-basins that cover an area of approximately 84,763 km² (Scottá et al., 2019). The Guaíba River is the main tributary of the Patos Lagoon (an area of 10,000 km²), which has access to the Atlantic Ocean. The navigable route within the river is approximately 56 km long and has a draft of 5.18 meters (17 feet).

The flow of liquid and solid discharges follows the alignment of the channel, where the highest amplitude waves also occur due to the greater depth. According to Nicolodi et al. (2013), based on numerically modeled data (SWAN) from wind directions and speeds between 1996 and 1997, wave heights ranged between 0.05 and 0.45 m, with periods between 0.8 s and 1.8 s.

The study area has eight port terminals. In 2022, 5 million tons of cellulose, oilseeds, fertilizers, containers, and chemical products were recorded in port transport (Agência Nacional de Transportes Aquaviários, 2024). The red rectangle (Figure 1, panel D) highlights the Port of Porto Alegre, which supplies the state's capital, Porto Alegre. Since 2022, the Environmental Management Program of the Port of Porto Alegre, a partnership (cooperation) between Portos RS and UFRGS, has aimed to bring sustainable development and significant improvements to the port and adjacent waterways, of which this study is a component.

Figure 1
Location map of the study area. (A) South America; (B) Drainage basin boundaries; (C) Lagoa dos Patos; (D) Guaíba River and navigation channel.

Despite the strong anthropogenic pressure and the various uses associated with this water body, one notable factor is the lack of available data and published studies (Scottá et al., 2019). This statement is also true regarding the absence of a database on navigation accidents and a better understanding of the safety conditions of the waterway.

Data and analyses performed

The methodology applied in this work involved the use of numerical modeling, publicly accessible news reports, as well as the acquisition, processing, and critical analysis of meteorological and hydrodynamic data, as presented in Figure 2.

Figure 2
Methodology flowchart from the top: data collection sources, analytical processes and output generation applied data.

It can be observed that the black and gray elements show the initial information and the databases used, respectively. The orange elements represent the obtained data, while the dark blue ones represent the data processing steps. The light blue elements indicate which numerical modeling modules available in the SisBaHiA application were used. The yellow elements show the results obtained through each step in the methodology, thus completing the flowchart.

Fog analysis

The horizontal visibility data were obtained for the region of Salgado Filho Airport. The data series were obtained directly from the ICEA (Institute of Airspace Control), in the Surface Data Research Division of the Brazilian Air Force. Visibility data is provided hourly in decameters when visibility conditions are less than 10,000 meters.

Another series of data associated with this analysis consisted of fog alerts from the METEOGRAM of the Brazilian Air Force’s Meteorological Network (REDEMET). From the analysis of a series from 01/01/2003 to 31/05/2023, it was verified that, as expected, horizontal visibility is the main factor for fog alert occurrence. It was observed that the alert was issued when visibility dropped below approximately 4000 meters.

For this, a routine of calculations was carried out, considering the existence of the fog event when the recorded visibility was equal to or less than 4000 meters, with the potential to harm navigation safety. The interval between the start and end of the fog event was also determined, as well as the lowest visibility recorded during this period for assessing the influence of the phenomenon on the analyzed navigation accident.

Wind analysis

The wind data used in this study were obtained from the ICEA website, in the Surface Data Research Division, for the region of Salgado Filho Airport. The available wind series (direction and intensity) are given in knots, with direction relative to the azimuth in degrees, measured at a height of 10 meters (Nicolodi et al., 2013).

For each reported navigation accident, historical wind series were obtained for a 30-day period: 25 days prior and 5 days following the accident. This data series was used as input data in the numerical model to estimate currents and waves in the waterway.

Hydrodynamic analysis through modeling

The analysis of the hydrodynamic parameters of the Guaíba River on the days of groundings was performed using the hydrodynamic model and wave generation model, both computational modules of the numerical model SisBaHiA (Environmental Hydrodynamics Base System), developed by the Coastal and Ocean Engineering Area of the Ocean Engineering Program (COPPE/UFRJ). The input data for the modeling were: flow, level, and wind.

The flow data used in this study were obtained from the study conducted by Fick et al. (2022), where the author used the historical level series obtained from the Praça da Harmonia gauge (period between 1941 and 2017) to generate the flow history. Along with this data, flow data for the Guaíba River were used, generated by the equation adjusted from flow and level data collected by Scottá et al. (2020) at the Cais Mauá C6 gauge (between 2014 and 2022), which, together with the previous series, cover all the years of groundings.

The level data used in this study were obtained from two distinct points in the Guaíba River. The data used until 2022, which covers up to the eighth grounding, were obtained from the station located at Ponta dos Coatis, identified by code 87500020, available on the HIDROWEB site. The level used for the ninth accident was obtained from Praia da Pedreira, with code 87242020, available on the HIDRO-TELEMETRIA site of the National Water Resources Information System (SNIRH).

Figure 3 presents the main points for data entry and acquisition along the waterway. Salgado Filho Airport is indicated as the location where wind and horizontal visibility data were obtained. Ponta dos Coatis and Praia da Pedreira are the locations where level data used in the numerical model were acquired.

Figure 3
Data acquisition locations for hydrological modeling.

The SisBaHiA hydrodynamic model is the fundamental basis for simulating the circulation of water bodies, using the FIST3D model, which relies on filtering techniques to model turbulence. It consists of two modules (2DH and 3D) to represent homogeneous and large-scale flows. Its spatial discretization optimizes the modeling of complex contours and bathymetries, combining bi-quadratic quadrangular finite elements, with the possibility of using quadratic triangular finite elements or a combination of both. The temporal discretization scheme is implicit, allowing results in 3D or 2DH depending on the input data. This enables the simulation of hydrodynamic circulation under different meteorological and hydrodynamic conditions. The system considers free surface elevation as a boundary condition, distinguishing between open boundaries, which allow calculated flow to pass through, and closed boundaries, which require specific values for flow rate or velocity (Universidade Federal do Rio de Janeiro, 2025).

The SisBaHiA Wave Generation Model simulates the formation of waves generated by permanent or variable winds, assessing whether their development is limited by fetch or duration. The mechanism governing wave generation involves the transfer of momentum from the wind to the water surface, influenced by three main factors: wind speed, duration, and the area over which the wind blows. Wave forecasting considers that, under constant wind conditions, wave heights increase until reaching the state of a fully developed sea, where the energy transferred from the air to the water surface is entirely dissipated by wave breaking. In this state, the maximum wave height that can be sustained by a given wind is produced. Based on wind records, the model calculates, at each specified time interval, the distribution of wave heights and the corresponding bottom stresses within the modeling domain (Universidade Federal do Rio de Janeiro, 2025).

For the implementation of these models, a mesh was created using the bathymetry of the Guaíba River, in addition to flow data from the Jacuí, Caí, Sinos, and Gravataí Rivers, the level at Itapuã, and the previously mentioned wind data. The mesh used in SisBaHiA for this study was defined during the preparation of the II Complementary Report on Impact Assessment of the Socioenvironmental Project ETE Serraria (Lersch et al., 2013). In its preparation, data from Nautical Charts 2113 and 2111 were used, adopting an equivalent bed roughness (ε) of 0.025 m for the entire modeled domain for simplification purposes, due to the dynamics of the sediments that make up the riverbed. The mesh is composed of finite elements, with a total of 1,202 quadrangular elements and 5,787 nodes. The bathymetric depths used are based on the nautical chart 2111 (Lersch et al., 2013). Figure 4 represents the mesh and bathymetry used.

Figure 4
Representation of the adopted mesh and bathymetry in the present study.

Simulated scenarios of navigation accidents

The scenarios aimed to simulate the hydrodynamics and wave generation for each day of grounding, covering a total of 30 days. The analysis of fog occurrences and wind was performed as described earlier.

Table 1 presents the temporal configuration used in the numerical model, including the start and end dates of the simulation, as well as the grounding date. Simulations were carried out for a minimum of 21 days before the accident date to avoid results near the initial days of the simulations, which are susceptible to numerical errors due to the model’s initial transition. Additionally, the location of the accident along the waterway and the reported cause for the accident are also presented.

Table 1
Temporal parameters of navigation accidents for numerical simulations.

Grounding	Numerical Simulation		Grounding Date	Location	Reported Cause
	Start Date	End Date
1	14/09/2007	13/10/2007	08/10/2007	Canal Pedras Brancas (ZS)	Mechanical Failure
2	26/05/2008	24/06/2008	18/06/2008	Canal Pedras Brancas (ZS)	Navigation Error/Fog
3	19/07/2011	17/08/2011	12/08/2011	Cais Navegantes	Current
4	07/08/2013	05/09/2013	31/08/2013	Canal do Cristal (PMB)	Mechanical Failure
5	02/08/2015	31/08/2015	26/08/2015	Farol de Itapuã	Navigation Error
6	27/09/2016	26/10/2016	22/10/2016	Canal do Leitão (ZS)	Navigation Error
7	29/12/2020	27/01/2021	22/01/2021	Cais Mauá	Evasive Maneuver outside the channel
8	27/12/2021	25/01/2022	20/01/2022	Canal Pedras Brancas (ZS)	Maneuver in low water level/Fog
9	25/05/2023	23/06/2023	15/06/2023	Ilha do Junco (Itapuã)	Cyclone Passage and Mechanical Failure

ANALYSIS AND RESULTS

Figure 5 shows the location of the nine reported accidents, all of which were found to be grounding incidents. Three of the groundings occurred in the Canal das Pedras Brancas, in the northern Guaíba, near Ponta do Dionísio. The numerical sequence indicates the chronological order of the accidents (Figure 5), which will be discussed individually.

Figure 5
Grounding locations with chronological sequence.

Hydrodynamic modeling results

Due to the spatial constraints of this study and in order to generally illustrate the methodology for obtaining results from the hydrodynamic and wave generation modules of SisBaHiA, the results related to grounding event 9 are presented below. However, the results, as well as the input data for each of the accidents, will be included in the appendices of this work. As a shared input between both modules, the time series of wind intensity and direction for the days surrounding the accident is shown in Figure 6. The horizontal axis of the graph indicates the simulation days, while the left vertical axis shows the wind speed, and the right vertical axis indicates the direction from which the wind originates. The grounding event 9 occurred between day 22 and 23 of the numerical simulation. The modules (hydrodynamic and wave generation) were fed with a 30-day wind data series, obtained from the meteorological station located at Salgado Filho International Airport, through the ICEA platform.

Figure 6
Wind speed and direction azimuth in grounding event 9.

Regarding hydrodynamic modeling, Figure 7A presents the time series of flow data used as boundary conditions for the hydrodynamic module of SisBaHiA. The data was organized into a series composed of daily flow values (m³/s) over a 30-day period, covering the grounding day. On the horizontal axis of the graph, the days included in the computational simulation are shown.

Figure 7
Grounding event 9: flow (A), current speed (B), water level (C) and wave heights (D) performed with SisBaHiA.

The results obtained from the numerical modules of SisBaHiA are presented graphically. After inserting the aforementioned input data and completing the configuration and parameterization of the accidents, the modeled results were extracted in representative time series. In Figure 7B, the system's hydrodynamic response is demonstrated through the time series of surface current velocities in the grounding 9 occurrence area. Figure 7C displays the variation in water level relative to the reference datum used in the nautical chart for configuring the bathymetry of the modeled domain. Finally, Figure 7D illustrates the time series of significant wave heights, resulting from simulations of the wind-driven wave generation module applied to the accident region.

The following sections detail each grounding event analyzed in this study, providing insights into the circumstances, causes, and contributing environmental factors. These events occurred in the Guaíba River waterway and adjacent channels, with varying influences from meteorological conditions (e.g., fog, wind) and hydrodynamic factors (e.g., currents, water levels, waves).

Grounding 1 - 08/10/2007

The first recorded grounding in this study occurred on October 8, 2007, at approximately 8:30 AM, in the Canal das Pedras Brancas, in the northern part of the waterway (Figure 4). According to Santos (2007), the vessel was transporting 4,000 tons of Naphtha. The cause indicated in the historical records was a main engine failure shortly after leaving the channel, with no cargo spillage. Environmental conditions indicated fog during the 2-hour period in the morning of the accident, which may have contributed to the grounding, according to a comparative analysis with data from Puhl & Michelon (2023).

Grounding 2 - 18/06/2008

The second grounding occurred on the morning of June 18, 2008, also in the Canal das Pedras Brancas, in the northern waterway. The cause reported in the news was fog, which surprised the ship loaded with 8,000 tons of fertilizer. The fog lasted 4 hours during the night and 1 hour in the morning, with a minimum visibility of 800 meters. As reported by Popa (2008), fog likely contributed to the accident. Hydrodynamic conditions indicated low risk, with currents of 0.1 m/s, a water level of 0.8 meters, and waves of 0.05 meters. Winds were below 2.5 m/s, typical in 36.6% of the analyses.

Grounding 3 - 12/08/2011

The third notable grounding occurred in the Guaíba waterway on August 12, 2011. The vessel, loaded with 14,000 tons of Potassium Chloride, grounded while leaving the navigation channel on its way to Cais Navegantes. The initial analysis by the Superintendence of Ports and Waterways of the State (SPH) suggested a possible maneuvering error, ruling out the low water level in Guaíba as the cause. Strong currents due to recent rains were also identified as contributing factors, according to the captain of the Port Authority. On the day of the incident, there was no fog recorded. Winds were below 3 m/s, and wave heights were about 0.02 meters. The water level was around 2 meters, according to SPH. The current velocity at the surface was approximately 0.6 m/s. These conditions, combined with the necessary maneuver for docking, suggest that the current in Guaíba at that moment may have contributed significantly to the grounding.

Grounding 4 - 31/08/2013

The fourth grounding in the Guaíba River waterway occurred on August 31, 2013. The vessel grounded in the Canal do Cristal due to a mechanical failure while transporting 7,000 tons of barley. According to Wink (2013), the attempt to repair the mechanical failure resulted in the loss of control by the captain, causing the vessel to veer out of the channel. On the day of the grounding, winds were light in the morning, with maximum speeds of 1.5 m/s, waves were low, around 0.05 meters, and the water level in the region was 1.6 meters, which did not indicate a grounding risk. However, the current speed reached 0.6 m/s, considering an average discharge of 4,367 m³/s. Although lower than in other cases, this current could still have influenced the vessel's movement, especially considering the mechanical failure. Therefore, the current force was a determining factor in the fourth accident.

Grounding 5 - 26/08/2015

The fifth grounding in the Guaíba River occurred near the Itapuã lighthouse on August 26, 2015, around 7:00 AM. According to Vasconselos (2015), the cause was a navigation error, evidenced by the sudden deviation of the vessel's course. Initial hypotheses of mechanical failure or contact with a sandbank were ruled out, as the location has natural guides and is recognized as hazardous. Meteorological and hydrodynamic analyses for the day did not indicate fog in the region in the morning, winds exceeding 3 m/s, or significant waves. The current speed was around 0.3 m/s, with a water level of 0.8 meters, presenting a low grounding risk. Thus, it is likely that the meteorological and hydrodynamic conditions did not contribute to the accident, confirming that it was the result of a navigation error.

Grounding 6 - 22/10/2016

The sixth grounding analyzed in this study occurred in the central area of the waterway, in the Canal do Leitão, on October 22, 2016, in the early evening. The captain made a wrong turn when attempting to dock a gas cargo, as reported by Klein (2016) and the Redação Portal Marítimo (2016). After the vessel was removed, it was anchored for inspection, which revealed no significant damage or leaks. Strong winds at the time of the grounding, estimated to have occurred in the early evening, reached up to 9.5 m/s from the Northeast, and waves reached 0.2 meters. The current speed, at about 0.5 m/s, was lower than the measurements made by Scottá et al. (2020) in the same area on the day of the grounding, which recorded values of 0.7-1.1 m/s near the grounding location. The measured discharge was 14,040 m³/s, representing the maximum discharge condition in this system. These meteorological and hydrodynamic conditions likely contributed to the grounding, along with the navigation error.

Grounding 7 - 22/01/2021

The seventh grounding incident in the Guaíba waterway occurred on the morning of January 22, 2021, in front of Cais Mauá. The vessel, loaded with 10,350 tons of fertilizer, grounded after leaving the navigation channel to allow two smaller vessels to pass, classified as a navigation error according to Correio do Povo (2021). The Superintendence of the Port of Rio Grande ruled out the low water level in Guaíba as the cause, considering it normal for that time of year. No fog was recorded at the time of the grounding. The water level in the region was 0.4 meters, representing a high risk of grounding. The current speed was around 0.2 m/s, with waves less than 0.1 meters. Winds blew from the East at about 7 m/s. These meteorological and hydrodynamic conditions do not appear to have contributed significantly to this incident, with the wind possibly playing a minor role. The primary cause was attributed to an evasive maneuver to allow other vessels to pass, indicating that the conditions in the Guaíba River at that moment did not present significant navigation risks.

Grounding 8 - 20/01/2022

The eighth grounding recorded in Guaíba occurred on January 20, 2022, in the Canal das Pedras Brancas, where groundings also occurred in 2007 and 2008. According to Campos (2022), the vessel, carrying 300 tons of soybeans bound for Rio Grande, attempted to avoid sandbanks due to the low water level in the Guaíba River and the occurrence of fog but ended up grounding on a rocky bottom. Hydrodynamic conditions at the grounding location showed a water level ranging from 0.16 meters to 0.24 meters, considered very high risk for accidents. On the other hand, fog was not confirmed on the day of the grounding, as suggested in the report. Other forces, such as winds and currents, were insignificant in causing the grounding. Therefore, although no fog was recorded, the low water level presented a significant risk of accident, corroborating the officially reported cause of the incident.

Grounding 9 – 15/06/2023

The ninth grounding in the Guaíba River occurred during the passage of a cyclone, likely on June 16, 2023, not June 15 as initially reported. The vessel, carrying 2 million liters of heavy fuel oil, grounded on Ilha do Junco, near Itapuã. Although fog was not confirmed, the intense rain associated with the cyclone may have reduced visibility in the Porto Alegre region. Winds on the day of the incident were predominantly from the Southeast, with intensities between 5 m/s and 6 m/s throughout the day, increasing to 10.8 m/s the next day. Currents also increased in speed, reaching about 0.5 m/s at noon on June 16, coinciding with the peak discharge of the Guaíba River during that period.

The water level in the grounding area rose significantly, from about 0.8 meters to 1.35 meters between June 15 and 16, due to increased discharge caused by rain and winds associated with the cyclone. Wave heights also increased, reaching approximately 0.28 meters at noon on June 16, within the range observed by Nicolodi et al. (2013) for July.

Based on these analyses, it is clear that the meteorological and hydrodynamic conditions caused by the passage of the cyclone significantly contributed to the grounding of the vessel Papoula.

Summary of the accidents and discussion

In Groundings 1 (2007) and 2 (2008), fog appeared to be the likely contributing factor to the accidents (Table 2). In Groundings 3 (2011) and 4 (2013), only the current speed appeared to have a likely contribution to the grounding. In 2015 (Grounding 5) and 2021 (Grounding 7), the natural factors assessed in the study did not contribute to the accidents. In Grounding 8, which occurred in 2021, the low water level was the determining factor for the occurrence. Finally, the intensity of the winds combined with the force of the current and wave action were the likely natural causes that contributed to the occurrence of Groundings 6 and 9.

Table 2
Analysis of meteorological and hydrodynamic conditions during grounding incidents (Wind m/s, Water Level m, Surface Current Velocity m/s, Wave Height m, Average Flow m³/s).

Cases	Min. Horizontal Visibility (m)	Wind Speed (m/s)	Water Level (m)	Current Speed (m/s)	Wave Heights (m)	Flow Average Rate (m3/s)	Location	Environment influence
1	3,000	5	1.2	0.15	0.05	1,563	Canal das Pedras Brancas	Fog
2	800	2.5	0.8	0.1	0.05	1,032	Canal das Pedras Brancas	Fog
3	-	3	2	0.6	0.02	5,052	Cais Navegantes	Current Speed
4	3,900	1.5	1.6	0.6	0.05	4,367	Canal do Cristal	Current Speed
5	3,000	3	0.8	0.3	0.1	3,303	Farol de Itapuã	No environment influence
6	-	9.5	1.6	0.5	0.2	7,089	Canal do Leitão	Wind, Level and Current
7	-	7	0.4	0.2	0.05	313	Cais Mauá	No environment Influence
8	-	5	0.16	0.15	0.1	196	Canal das Pedras Brancas	Water Level
9	-	10.75	1.35	0.5	0.3	7,101	Ilha do Junco	Wind, Level and Current

It is noteworthy that meteorological and hydrological factors probably contributed to the groundings in most cases. The complexity of the waterway is also manifested through various forces that can trigger accidents, such as winds, waves, flow, fog, and low water levels. The study further emphasizes that these forces can occur simultaneously, increasing the risk of incidents. In the analysis of two specific cases, it was found that the interaction between winds, currents, and waves likely contributed to these occurrences.

Maritime accidents are complex processes, where typically there is not just a single factor involved (Coraddu et al., 2020; Hetherington et al., 2006). While existing reports attribute accidents to mechanical failures or human error, without examining the potential environmental factors, this study introduces a novel approach to investigating cause by focusing on environmental conditions affecting waterway safety. It should be noted that this research does not address human or mechanical factors due to data limitations..

Several studies point to the underreporting of accidents and the difficulty of having a consistent database for detailed analyses (Bye & Aalberg, 2018; Eliopoulou et al., 2016; Hassel et al., 2011; Psarros et al., 2010), regardless of global maritime accident data or localized waterway data. The construction of consistent databases containing refined location information, including details on oceanographic conditions, vessels in transit, their characteristics, and incidents (Heij & Knapp, 2015), can provide better conditions for a detailed investigation of the waterway.

When comparing the findings of this study with research on other inland waterways, both similarities and notable differences emerge. Studies such as Hossain et al. (2014) on the inland water transport system in Bangladesh demonstrate that groundings and collisions in heavily trafficked rivers are often linked to structural issues in the system, such as high sedimentation rates, inadequate infrastructure, and lack of navigational aids. These elements similarly contribute to accident risks in the systems examined in the current study.

In the case of Vietnam, Ha et al. (2023) developed a safety evaluation model based on risk elements (REs), emphasizing human error, operational limitations, and equipment maintenance, highlighting crew negligence as the main cause of accidents — a factor not directly examined here due to lack of data but widely recognized in international literature

Furthermore, Zhou et al. (2020) provide a quantitative analysis of wind and current effects in European port areas, demonstrating how these environmental factors influence on ship behavior using AIS data — an approach that reinforces the findings of this study by objectively confirming the critical role of environmental variables in navigation safety.

Thus, although the geographic and operational contexts differ, the studies analyzed support the importance of incorporating environmental factors into grounding risk models for inland waterways, while also revealing a shared challenge: the lack of systematic accident data and the need for integrated, multi-causal analysis approaches.

Beyond the environmental factors examined, Brazil's regulatory framework for navigation safety merits consideration. The Brazilian Maritime Code (Law No. 9.537/1997) (Brasil, 1997) and NORMAM-302 (Brasil, 2023) designate the Brazilian Navy as the authority responsible for waterway safety oversight, encompassing accident investigations, vessel inspections, and enforcement of navigation regulations.

NORMAM-302, in particular, establishes the procedures for Administrative Inquiries into Navigation Accidents, reinforcing the Navy’s role in identifying causes and preventing future incidents. However, this study demonstrates that environmental conditions can be systematically reconstructed through data analysis, providing a complementary approach to official investigations. This study offers an interpretative analysis of potential environmental contributors, without claiming to define accident causes. These findings enhance the paper's technical contribution by advancing risk assessment methodologies and supporting regulatory improvements for inland waterway safety.

CONCLUSION

Analysis of the nine investigated grounding incidents revealed critical vulnerability points and patterns along the Guaíba River waterway. The investigations demonstrated that multiple environmental factors, such as fog, current, waves, and wind, significantly contributed to these accidents in most cases, often acting in combination to create hazardous navigation conditions.

The study's analysis identified the Pedras Brancas Channel as the most critical grounding hotspot along the waterway. Three confirmed grounding accidents occurred at this location, each under distinct meteorological and hydrodynamic conditions, in different years, and involving different vessels.

Analysis of grounding incidents on the Guaíba River identified the following critical environmental thresholds for navigation safety: (a) surface current speeds exceeding 0.5 m/s, (b) wind speeds above 7 m/s, water levels below 0.4 m, and (c) significant wave heights above 0.2 m, particularly affecting small motorized and non-motorized vessels.

This study analyzes contributing factors to navigation accidents in specific waterway areas, with dual objectives: (a) to generate actionable data for improving safety and management of Brazil's navigable waterways and ports, and (b) to establish correlations between accident occurrences and environmental factors—including meteorological conditions and geographic features—to identify risk patterns. These findings aim to support evidence-based preventive measures and inform more effective risk management policies for port and maritime authorities

To improve operational safety, port authorities and policymakers (Capitânia dos Portos e a Agência Nacional de Transportes Aquaviários - ANTAQ) must adopt real-time monitoring systems of meteorological and hydrodynamic conditions, especially in high-risk zones like Canal das Pedras Brancas. Navigation regulations should be revised to reflect dynamic environmental thresholds, imposing stricter operational limits during hazardous conditions. To further mitigate grounding risks, investments in technological infrastructure are recommended, including: advanced nautical signaling systems throughout the waterway and implementation of a real-time monitoring network of the hydrodynamic (water levels and flow rates) and meteorological parameters (wind speed and direction), enabling to real time data availability for safety navigational decision making, recommended to further mitigate grounding risks.

A comprehensive approach to investigating navigation accidents is recommended, recognizing their complexity and avoiding simplifications. For future work, it is essential to incorporate systematic data on human error and mechanical factors, in addition to those highlighted in the reports. Furthermore, overcoming the challenges of underreporting data is essential, investing in the development of robust and integrated databases. The creation of detailed databases, with accurate information on accident location, meteorological and hydrological conditions, vessel characteristics, and operational context, is fundamental for an effective investigation into waterway safety and guiding targeted, data-driven policy decisions.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the financial support provided by Portos RS, a public company, through the Programa de Gestão Ambiental Portuária - Porto Alegre Port (PGA-POA) (Project 2.20.2126/423, Agreement No. 1117/2021), administered by the Universidade Federal do Rio Grande do Sul (UFRGS), which enabled this research.

DATA AVAILABILITY STATEMENT

Research data is only available upon request.

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Edited by

• Editor-in-Chief:
  Adilson Pinheiro

• Associated Editor:
  Iran Eduardo Lima Neto

Publication Dates

• Publication in this collection
  17 Nov 2025
• Date of issue
  2025

History

• Received
  26 Feb 2025
• Reviewed
  28 July 2025
• Accepted
  26 Aug 2025