Park, Edward

The Amazon River basin harbors some of the world's largest wetland complexes, which are of major importance for biodiversity, the water cycle and climate, and human activities. Accurate estimates of inundation extent and its variations across spatial and temporal scales are therefore fundamental to understand and manage the basin's resources. More than fifty inundation estimates have been generated for this region, yet major differences exist among the datasets, and a comprehensive assessment of them is lacking. Here we present an intercomparison of 29 inundation datasets for the Amazon basin, based on remote sensing only, hydrological modeling, or multi-source datasets, with 18 covering the lowland Amazon basin (elevation <500 m, which includes most Amazon wetlands), and 11 covering individual wetland complexes (subregional datasets). Spatial resolutions range from 12.5 m to 25 km, and temporal resolution from static to monthly, spanning up to a few decades. Overall, 31% of the lowland basin is estimated as subject to inundation by at least one dataset. The long-term maximum inundated area across the lowland basin is estimated at 599,700 ± 81,800 km2 if considering the three higher quality SAR-based datasets, and 490,300 ± 204,800 km2 if considering all 18 datasets. However, even the highest resolution SAR-based dataset underestimates the maximum values for individual wetland complexes, suggesting a basin-scale underestimation of ~10%. The minimum inundation extent shows greater disagreements among datasets than the maximum extent: 139,300 ± 127,800 km2 for SAR-based ones and 112,392 ± 79,300 km2 for all datasets. Discrepancies arise from differences among sensors, time periods, dates of acquisition, spatial resolution, and data processing algorithms. The median total area subject to inundation in medium to large river floodplains (drainage area > 1000 km2) is 323,700 km2. The highest spatial agreement is observed for floodplains dominated by open water such as along the lower Amazon River, whereas intermediate agreement is found along major vegetated floodplains fringing larger rivers (e.g., Amazon mainstem floodplain). Especially large disagreements exist among estimates for interfluvial wetlands (Llanos de Moxos, Pacaya-Samiria, Negro, Roraima), where inundation tends to be shallower and more variable in time. Our data intercomparison helps identify the current major knowledge gaps regarding inundation mapping in the Amazon and their implications for multiple applications. In the context of forthcoming hydrology-oriented satellite missions, we make recommendations for future developments of inundation estimates in the Amazon and present a WebGIS application (https://amazon-inundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.

Ecotourism in national parks of developing countries is increasingly recognised as a promising option to achieve sustainable development goals, regardless, might imply various paradoxical managerial challenges. This paper, therefore, seeks to contribute a methodological framework utilising ES-based social landscape metrics (SLM) to address the potential barriers in managing ecotourism-integrated multi-functional national parks. We present a mixed-method case study in Vietnam's Tram Chim National Park (TCNP), conducted via semi-structural interviews and PGIS with tourists and locals. Multiple key informants, i.e. TCNP's authorities were also interviewed to provide their managerial insights and assist in verifying the PGIS results obtained from the tourists and locals. Via the quantified and mapped SLMs, the study reveals the differences between tourists and locals in terms of how and where they perceive and appreciate the intangible values of TCNP. Through spatial statistics, we reported important spatial correlations (i) between different categories of Ecosystem Services (ES) and (ii) between ES richness and diversity on different TCNP's land covers. As a contribution to the decision-making outlook, we remarked potential areas to expand of ecotourism activities based on the spatial hot and cold spots. This study concludes by highlighting opportunities for future research in expanding on socio-geographical assessments of ES, especially in the fields of ecotourism.

The Vietnamese Mekong Delta (VMD) has experienced severe morphological changes for decades, resulting in serious social, economic, and environmental consequences. Several natural and anthropogenic factors have contributed to the increasing rate of riverbed incision along the VMD. While previous studies have assessed riverbed incisions in specific affected regions or within limited timeframes, a comprehensive analysis of long-term spatiotemporal variations in incised sediment volumes across the entire delta has been lacking. This study quantitatively evaluated the spatial and temporal morphological changes in the VMD utilizing bathymetric data from 1998 to 2020. Additionally, susceptibility zones, categorized into seven classes for incised and accreted sediment volumes, were delineated considering the influence of sand mining activities. Furthermore, this study pioneers the quantification of sand mining contributions to riverbed incisions along the VMD. The analysis revealed pronounced and irregular morphological alterations in the delta channels over the 22 years of the study. The estimated net annual incision volumes for the entire region were -119 Mm3/year, −69 Mm3/year, and -66 Mm3/year for the 1998–2005, 2005–2017, and 2017–2020 time intervals, respectively. Between 2017 and 2020, the dynamic processes intensified notably, with some areas experiencing either high incision (up to −13 m/year) or high accretion (up to 11 m/year). Intriguingly, most incise-prone areas were partly situated within regions associated with sand mining. The contribution of licensed sand mining to annual net riverbed incisions increased from 27.7 % in 2005–2017 to 35.3 % in 2017–2020. This study highlights the influence of sand mining on exacerbating the vulnerability of different areas within the VMD and provides valuable insights for effective sediment management strategies.

As of October 8th, 2020, the number of confirmed cases and deaths in Brazil due to COVID-19 hit 5,002,357 and 148,304, respectively, making the country one of the most affected by the pandemic. The State of São Paulo (SSP) hosts the largest number of confirmed cases in Brazil, with over 1,016,755 cases to date. This study was carried out to investigate how the social distancing measures could have influenced the Ibitinga reservoir's water transparency in São Paulo State, Brazil. We hypothesize that although the city's drainage is the major reservoir's input, as opposed to what has been reported elsewhere, the effect of extensive lockdown in the city of São Paulo due to COVID-19 is marginal on the water transparency. A time series of OLI/Landsat-8 images since 2014 were used to estimate the Secchi Disk Depth (ZSD). The COVID-19 cases and deaths (per 100,000 inhabitants), and social isolation index were used to find links between the ZSD and COVID-19. The results showed that the highest ZDS (higher than 1.6 m) occurred during the dry season (Austral autumn and beginning of Austral winter) and the lowest (0.4–0.8 m) during March 2020 (end of Austral summer). Paired sample t-Tests between images of 2020 and all the others showed that April 20th values were not different from that of June 14th, April 17th and March 18th. ZSD values from May 20th were not statistically different from May 14th and April 15th; June 20th values were not different from June 14th; and March 20th values were statistically different from all. We therefore conclude that, based on satellite data, the lockdown in SSP unlikely have influenced the water transparency in the Ibitinga reservoir.

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed atastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13×106m2), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.

The concept of cultural ecosystem services has been increasingly influential in both environmental research and policy decision making, such as for urban green spaces. However, its popular definitions tend to conflate “services” with “benefits”, making it challenging for planners to employ them directly to manage urban green spaces. Thus, attempts have been made to redefine cultural ecosystem services as the function of cultural activities in environmental spaces which result in people’s enjoyment of cultural ecosystem benefits. The operability of such a redefinition needs to be evaluated, which this study seeks to achieve with Bishan-Ang Mo Kio Park in Singapore presenting itself as a prime case study research area. Transdisciplinary mixed methods of a public participation geographic information system, which leverages on spatial data from public park users, and social media text mining analysis via Google reviews were used. A wealth of cultural ecosystem services and benefits were reported in the park, especially the recreational and aesthetic services and experiential benefits. Policy and methodological implications for future research and urban park developments were considered. Overall, this paper would recommend the employment of the redefined cultural ecosystem services approach to generate relational, data-driven and actionable insights to better support future urban green space management.

Vietnam Mekong Delta (VMD), the country's most important food basket, is constantly threatened by drought-infused salinity intrusion (SI). The SI disaster of 2020 is recognized as the worst in recent decades, hence inspiring this perspective article. The authors' viewpoints on the disaster's impacts and causes are presented. The arguments presented are mainly drawn from (i) up-to-date publications that report on the recent SI intensification in the VMD and (ii) the power spectral analysis results using water level data. We verified the intensifying SI in the VMD both in its frequency and magnitude and remarked on four of the key SI drivers: (i) upstream hydropower dams, (ii) land subsidence, (iii) the relative sea-level rise, and (iv) riverbed sand mining. Also, a non-exhaustive yet list of recommendable management implications to mitigate the negative effects of the SI is contributed. The mitigation measures must be realized at multiple scales, ranging from pursuing transboundary water diplomacy efforts to managing internal pressures via developing early warnings, restricting illegal sand mining activities, alleviating pressures on groundwater resources, and diversifying agriculture.