A novel framework for the use of remote sensing for monitoring catchments at continental scales

Remote sensing of water colour in small southeastern Australian waterbodies

The colour of a waterbody may be indicative of the water quality or environmental change. Monitoring water colour can therefore be an important proxy for various waterbody processes. To this aim, satellites are increasingly being used as viable alternatives to field measurements. This study investigates whether water colour derived from satellites is an effective predictor of spatial and temporal patterns of water quality or environmental change in small waterbodies and can be used to explain the drivers of trends in these waterbodies. As a case study, 145 small waterbodies (<1 km2) in the greater Melbourne, south-eastern Australia were analysed to understand water colour spatio-temporal patterns using Sentinel-2 and Landsat 5, 7 and 8 satellite surface reflectance imagery over a period of 30 years. We found that the baseline water colour of small waterbodies in the greater Melbourne region has a dominant wavelength in the green to yellow region of the visible spectrum (λd ranging from 532 to 578 nm). Waterbody design factors and broader climate factors were also tested to understand the spatial variation of baseline water colour. Macrophyte ratio and the shoreline development index were shown to be the primary waterbody design factors that affect water colour. Some waterbodies are responsive to climate variability based on investigating how climate factors impact the water colour variability. Local climate factors had more impact than regional climate factors. Results from this study highlight how water colour could be used as a proxy for waterbody health assessment and how spatio-temporal variations in water colour can be used to assess environmental trends.

Spatio-temporal evolution and influencing factors of synergizing the reduction of pollution and carbon emissions - Utilizing multi-source remote sensing data and GTWR model

Grasping current circumstances and influencing components of the synergistic degree regarding reducing pollution and carbon has been recognized as a crucial part of China in response to the protection of the environment and climate mitigation. With the introduction of remote sensing night-time light, CO₂ emissions at multi-scale have been estimated in this study. Accordingly, an upward trend of "CO₂-PM_2.5" synergistic reduction was discovered, which was indicated by an increase of 78.18% regarding the index constructed of 358 cities in China from 2014 to 2020. Additionally, it has been confirmed that the reduction in pollution and carbon emissions could coordinate with economic growth indirectly. Lastly, it has identified the spatial discrepancy of influencing factors and the results have emphasized the rebound effect of technological progress and industrial upgrades, whilst the development of clean energy can offset the increase in energy consumption thus contributing to the synergy of pollution and carbon reduction. Moreover, it has been highlighted that environmental background, industrial structure, and socio-economic characteristics of different cities should be considered comprehensively in order to better achieve the goals of "Beautiful China" and "Carbon Neutrality".

Remote sensing to detect harmful algal blooms in inland waterbodies

Harmful algal blooms (HABs) are an issue of concern for water management worldwide. As such, effective monitoring strategies of HAB spatio-temporal variability in waterbodies are needed. Remote sensing has become an increasingly important tool for HAB detection and monitoring in large lakes. However, accurate HAB detection in small-medium waterbodies via satellite data remains a challenge. Current barriers include the waterbody size, the limited freely available high resolution satellite data, and the lack of field calibration data. To test the applicability of remote sensing for detecting HABs in small-medium waterbodies, three satellites (Planetscope, Sentinel-2 and Landsat-8) were used to understand how spatial resolution, the availability of spectral bands, and the waterbody size itself effect HAB detection skill. Different algorithms and a non-parametric method, Self-Organizing Map (SOM), were tested. Curvature Around Red and NIR minus Red had the best HAB detection skill of the 20 existing algorithms that were tested. Landsat 8 and Sentinel 2 were the best satellites for HAB detection in small to medium waterbodies. The most critical attribute for detecting HABs were the available satellite bands, which determine the detection algorithms that can be used. Importantly, algorithm performance was mostly unrelated to waterbody size. However, there remain some barriers in utilizing satellite data for HAB detection, including algae dynamics, macrophyte cover within the waterbody, weather effects, and the correction models for satellite data. Moreover, it is important to consider the match time between satellite overpass and sampling activities for calibration. Given these challenges, integrating regular sampling activities and remote sensing is recommended for monitoring and managing small-medium waterbodies.

Assessment of Palm Jumeirah Island’s Construction Effects on the Surrounding Water Quality and Surface Temperatures during 2001–2020

Climate change stressors like rising and warmer seas, increased storms and droughts, and acidifying oceans are rapidly threatening coastal zones, which are the world’s most densely inhabited places. This research assesses the effects of Palm Jumeirah Island (PJI) construction on its surrounding water quality and temperature, using Landsat-7 and 8 spectral and thermal bands for the years 2001, 2014, 2016, 2019, and 2020. To aid in this goal, the changes in water spectral reflectance was observed and interpreted, based on previous research and measurements, to discover the correlation between water quality and its spectral reflectance. Then, the sea surface temperature (SST) was calculated for the years under review and changes in water temperature were evaluated. Finally, the Green Normalized Difference Vegetation Index (GNDVI) and the Normalized Difference Turbidity Index (NDTI) were calculated to estimate water chlorophyll levels and water turbidity, respectively, and changes were observed and interpreted for the time period under review. The present study showed that the PJI construction not only increased the water reflectance in the 0.5–0.8 µm of wavelength, which can be considered to be the increase of suspended sediments and chlorophyll but the water temperature also increased by 7.5 °C during the 19 years. In addition, a gradual increase in the values of GNDVI (by 0.097–0.129) and NDTI (by 0.118~0.172) were observed. A drop in chlorophyll and suspended sediment spectral reflectance and GNDVI and NDTI values were also observed in 2020 compared to 2019 which can be attributed to the 63 to 82% decrease in tourists in Dubai in 2020 as a result of the COVID-19 pandemic. This study aims to draw attention to environmental issues by clarifying the effect of creating artificial islands in the sea and our analysis and results are a suitable reference for specialized hydrological and environmental studies based on spectral information and distance measurements, as presented in this paper.

A comprehensive review of catchment water quality monitoring using a tiered framework of integrated sensing technologies

Due to the growing threat of climate change, new advances in water quality monitoring strategies are needed now more than ever. Reliable and robust monitoring practices can be used to improve and better understand catchment processes affecting the water quality. In recent years the deployment of long term in-situ sensors has increased the temporal and spatial data being obtained. Furthermore, the development and research into remote sensing using satellite and aerial imagery has been incrementally integrated into catchments for monitoring areas that previously might have been impossible to monitor, producing high-resolution data that has become imperative to catchment monitoring. The use of modelling in catchments has become relevant as it enables the prediction of events before they occur so that strategic plans can be put in place to deal with or prevent certain threats. This review highlights the monitoring approaches employed in catchments currently and examines the potential for integration of these methods. A framework might incorporate all monitoring strategies to obtain more information about a catchment and its water quality. The future of monitoring will involve satellite, in-situ and air borne devices with data analytics playing a key role in providing decision support tools. The review provides examples of successful use of individual technologies, some combined approaches and identifies gaps that should be filled to achieve an ideal catchment observation system.

Soil salinization management for sustainable development: A review

The expansion of irrigated agriculture is of paramount importance to feed the burgeoning global population. However, without proper management, this expansion can result in environmental problems of irrigation-induced soil salinization. A recent FAO estimate reported that a large portion of total global soil resources are degraded and this problem is persistently expanding. Many irrigated areas of the world are facing the twin problems of soil salinization and waterlogging and presently over 20% of the total global irrigated area is negatively affected by these problems. And, if left unattended, this problem could expand to over 50% of the total global irrigated areas by 2050. The proper management of the aforementioned soil salinization is imperative for achieving most of the Sustainable Development Goals (SDGs) of the United Nations. For example, soil salinization management is vital for achieving the 'Zero Hunger' (SDG2) and 'Life on Land' (SDG15) among other SDGs. This paper provides a comprehensive review of different measures used for managing the environmental problems of soil salinization. All the possible sources of related and up to date literature have been accessed and over 250 publications were collected and thoroughly analyzed for this review. The centrality of the environmental problems is provided. The background of the problems, managing rising water table to control soil salinization, the role of drainage frameworks, the conjunctive use of diverse water sources, utilization of numerical models, and the use of remote sensing and GIS systems are described. And the application of the aforementioned techniques and methods in various case study regions across the globe are discussed which is followed by discussion and research gaps. Derived from the literature analysis and based on the identified research gaps, some key recommendations for future research have been made which could be useful for the stakeholders. The literature analysis revealed that an all-inclusive approach for dealing with the aforesaid environmental problems has been barely considered in the previous studies. Similarly, the continuing impacts of growing salt-tolerant plants on soil characteristics and the environment in total have not been widely considered in the previous investigations. Likewise, better irrigation practices and improved cropping systems along with the long-term environmental impacts of a particular approach has not been extensively covered in these studies. Also, previous studies have scarcely incorporated economic, social, and environmental aspects of the salinization problem altogether in their analysis. The analysis suggested that an inclusive feedback-supported simulation model for managing soil salinization should be considered in future research as the existing models scarcely considered some vital aspects of the problem. It is also suggested to enhance the sensing methods besides retrieval systems to facilitate direct detection of salinization and waterlogging parameters at large-scales. The existing time-lag between occurrence and recording of various data is also suggested to improve in the future scenario by the usage of information from multiple satellites that lessens the problems of spatial resolution by increasing the system efficiency.

Classification of Australian Waterbodies across a Wide Range of Optical Water Types

Baseline determination and operational continental scale monitoring of water quality are required for reporting on marine and inland water progress to Sustainable Development Goals (SDG). This study aims to improve our knowledge of the optical complexity of Australian waters. A workflow was developed to cluster the modelled spectral response of a range of in situ bio-optical observations collected in Australian coastal and continental waters into distinct optical water types (OWTs). Following clustering and merging, most of the modelled spectra and modelled specific inherent optical properties (SIOP) sets were clustered in 11 OWTs, ranging from clear blue coastal waters to very turbid inland lakes. The resulting OWTs were used to classify Sentinel-2 MSI surface reflectance observations extracted over relatively permanent water bodies in three drainage regions in Eastern Australia. The satellite data classification demonstrated clear limnological and seasonal differences in water types within and between the drainage divisions congruent with general limnological, topographical, and climatological factors. Locations of unclassified observations can be used to inform where in situ bio-optical data acquisition may be targeted to capture a more comprehensive characterization of all Australian waters. This can contribute to global initiatives like the SDGs and increases the diversity of natural water in global databases.

Climate change rapidly warms and acidifies Australian estuaries

Climate change is impacting ecosystems worldwide. Estuaries are diverse and important aquatic ecosystems; and yet until now we have lacked information on the response of estuaries to climate change. Here we present data from a twelve-year monitoring program, involving 6200 observations of 166 estuaries along >1100 kilometres of the Australian coastline encompassing all estuary morphologies. Estuary temperatures increased by 2.16 °C on average over 12 years, at a rate of 0.2 °C year^-1, with waters acidifying at a rate of 0.09 pH units and freshening at 0.086 PSU year^-1. The response of estuaries to climate change is dependent on their morphology. Lagoons and rivers are warming and acidifying at the fastest rate because of shallow average depths and limited oceanic exchange. The changes measured are an order of magnitude faster than predicted by global ocean and atmospheric models, indicating that existing global models may not be useful to predict change in estuaries.

Developing an empirical model from Landsat data series for monitoring water salinity in coastal Bangladesh

This study aims to develop an empirical model from Landsat data series to monitor the water salinity of coastal Bangladesh efficiently. Such a model can substitute expensive conventional techniques for assessing remote water quality. A set of equations connecting sensors 5 TM and 8 OLI were generated using multiple regression analysis. Radiometric and atmospheric corrections were carried out to enhance the quality of satellite images. Total 13 compositions of different bands including blue, green and red were considered to find the Coefficient of Determination (r²) with the field level EC (electrical conductivity) values collected from 74 sampling locations. Salinity data mainly EC values of coastal water were collected from primary and secondary sources. Considering the r² values, significant band compositions were identified and then employed to generate linear equations. Such equation for Landsat 5 TM could detect water salinity (i.e. EC) accurately of around 82%. Similarly, the r² value for Landsat 8 OLI was found as 0.76 that can confirm the applicability of Landsat data series to detect the change of salinity level of coastal water for a long period. The availability of coastal water was delineated by NDWI whereas salinity level was assessed using the developed equations for the year 2001 and 2019. Interestingly, it was observed that coastal areas having lower level of EC almost vanished whereas those of having higher level of EC were increased significantly between 2001 and 2019. Such increase in coastal water salinity is the result of combined effects of climatic and anthropogenic factors, which can pose a considerable risk to the coastal inhabitants including freshwater scarcity, food insecurity, and health hazard.