This study provides a comprehensive review of the efforts utilized in the measurement of water quality parameters (WQPs) with a focus on total dissolved solids (TDS) and total suspended solids (TSS). The current method used in the measurement of TDS and TSS includes conventional field and gravimetric approaches. These methods are limited due to the associated cost and labor, and limited spatial coverages. Remote Sensing (RS) applications have, however, been used over the past few decades as an alternative to overcome these limitations. Although they also present underlying atmospheric interferences in images, radiometric and spectral resolution issues. Studies of these WQPs with RS, therefore, require the knowledge and utilization of the best mechanisms. The use of RS for retrieval of TDS, TSS, and their forms has been explored in many studies using images from airborne sensors onboard unmanned aerial vehicles (UAVs) and satellite sensors such as those onboard the Landsat, Sentinel-2, Aqua, and Terra platforms. The images and their spectral properties serve as inputs for deep learning analysis and statistical, and machine learning models. Methods used to retrieve these WQP measurements are dependent on the optical properties of the inland water bodies. While TSS is an optically active parameter, TDS is optically inactive with a low signal–noise ratio. The detection of TDS in the visible, near-infrared, and infrared bands is due to some process that (usually) co-occurs with changes in the TDS that is affecting a WQP that is optically active. This study revealed significant improvements in incorporating RS and conventional approaches in estimating WQPs. The findings reveal that improved spatiotemporal resolution has the potential to effectively detect changes in the WQPs. For effective monitoring of TDS and TSS using RS, we recommend employing atmospheric correction mechanisms to reduce image atmospheric interference, exploration of the fusion of optical and microwave bands, high-resolution hyperspectral images, utilization of ML and deep learning models, calibration and validation using observed data measured from conventional methods. Further studies could focus on the development of new technology and sensors using UAVs and satellite images to produce real-time in situ monitoring of TDS and TSS. The findings presented in this review aid in consolidating understanding and advancement of TDS and TSS measurements in a single repository thereby offering stakeholders, researchers, decision-makers, and regulatory bodies a go-to information resource to enhance their monitoring efforts and mitigation of water quality impairments.

Measurement of Total Dissolved Solids and Total Suspended Solids in Water Systems: A Review of the Issues, Conventional, and Remote Sensing Techniques

Water is an imperative part of the Earth and an essential resource in human life and production. Under the effects of climate change and human activities, the spatial and temporal distribution of water bodies has been changing, and the shortage of water resources is becoming increasingly serious worldwide. Therefore, the monitoring of water bodies is indispensable. Remote sensing has the advantages of real time, wide coverage, and rich information and has become a brand-new technical means to quickly obtain water information. This study summarizes the current common methods of water extraction based on optical and radar images, including the threshold method, support vector machine, decision tree, object-oriented extraction, and deep learning, as well as the advantages and disadvantages of each method. These methods were applied to the Huai River Basin in China and Nam Co on the Qinghai-Tibet Plateau. The extraction results show that all the aforementioned approaches can obtain reliable results. Among them, the threshold segmentation method based on normalized difference water index is more robust than others. In the water extraction process, there are still many problems that restrict the accuracy of the results. In the future, researchers will continue to search for more automatic, extensive, and high-precision water extraction methods.

https://www.mdpi.com/2073-4441/14/7/1148/pdf?version=1649315107

Satellite Detection of Surface Water Extent: A Review of Methodology

40-years of Lake Urmia restoration research: Review, synthesis and next steps.

/pdf/managing-lake-urmia-iran-for-diverse-restoration-objectives-1iwzefm543.pdf

Managing Lake Urmia, Iran for diverse restoration objectives: Moving beyond a uniform target lake level

Many saline lakes throughout the world are shrinking due to overexploitation of water in their drainage basins. Among them are two of the world’s largest saline lakes, the U.S.A.’s Great Salt Lake, and Iran’s Lake Urmia. Here we provide a comparative analysis of the desiccation of these two lakes that provides insights on management decisions that may help save them and that are relevant to saline lake management worldwide. Great Salt Lake and Lake Urmia were once remarkably similar in size, depth, salinity, and geographic setting. High rates of population growth in both basins have fueled a demand for irrigated agriculture and other uses. In the Great Salt Lake basin, this development began in the late 1800’s and is continuing. The lake’s volume has decreased by 67%, with 75% of the loss driven by water development and 25% by a millennial drought which may portend the start of global climate change impacts. This has greatly increased salinities to 180 g·L−1 stressing the invertebrates in the lake on which birds depend. Only 1% of people in the basin are employed in agriculture; thus, reducing the demand for irrigation development. Population densities in the Urmia basin are double those of the Great Salt Lake basin, and 28% of people are employed in agriculture. These demographics have led to a rapid increase in reservoir construction since 2000 and the subsequent loss of 87% of Lake Urmia’s volume. The water development of Lake Urmia was later, but much faster than that of Great Salt Lake, causing Urmia’s salinity to increase from 190 to over 350 g·L−1 in just 20 years, with subsequent severe ecological decline. Dust storms from the exposed lakebeds of both systems threaten the health of the surrounding populations. To save these lakes and others will require: (1) transparent and collaborative involvement with local interest groups; (2) shifts away from an agricultural-based economy to one based on manufacturing and services; (3) consideration of the diverse ecosystem services of the lakes including mineral extraction, recreation, bird habitats in surrounding wetlands, and dust control.

/pdf/contrasting-management-and-fates-of-two-sister-lakes-great-1p3u1er6.pdf

Contrasting Management and Fates of Two Sister Lakes: Great Salt Lake (USA) and Lake Urmia (Iran)

Mapping the spatiotemporal variability of salinity in the hypersaline Lake Urmia using Sentinel-2 and Landsat-8 imagery

The primary objective of this study was to identify a universal wastewater biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology (WBE). A total of 2,624 wastewater samples (41 weeks) were collected weekly during May 2021- April 2022 from 64 wastewater facilities across Missouri, U.S. Three wastewater biomarkers, caffeine and its metabolite, paraxanthine, and pepper mild mottle virus (PMMoV), were compared for the population normalization effectiveness for wastewater SARS-CoV-2 surveillance. Paraxanthine had the lowest temporal variation and strongest relationship between population compared to caffeine and PMMoV. This result was confirmed by data from ten different Wisconsin WWTPs with gradients in population sizes, indicating paraxanthine is a promising biomarker of the real-time population across a large geographical region. The estimated real-time population was directly compared against the population patterns with human movement mobility data. Of the three biomarkers, population normalization by paraxanthine significantly strengthened the relationship between wastewater SARS-CoV-2 viral load and COVID-19 incidence rate the most (40 out of 61 sewersheds). Caffeine could be a promising population biomarker for regions where no significant exogenous caffeine sources (e.g., discharges from food industries) exist. In contrast, PMMoV showed the highest variability over time, and therefore reduced the strength of the relationship between sewage SARS-CoV-2 viral load and the COVID-19 incidence rate, as compared to wastewater data without population normalization and the population normalized by either recent Census population or the population estimated based on the number of residential connections and average household size for that municipality from the Census. Overall, the findings of this long-term surveillance study concluded that the paraxanthine has the best performance as a biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology.

/pdf/population-normalization-in-sars-cov-2-wastewater-based-1uulypkb.pdf

Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Geochemistry and mineralization of the East Ridge ore zone in Mehdiabad zinc-lead- barite deposit, Yazd Province, Central Iran 

Revisiting bathymetry dynamics in Lake Urmia using extensive field data and high-resolution satellite imagery

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Mapping the spatiotemporal variability of salinity in the hypersaline Lake Urmia using Sentinel-2 and Landsat-8 imagery

Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Geochemistry and mineralization of the East Ridge ore zone in Mehdiabad zinc-lead- barite deposit, Yazd Province, Central Iran

Revisiting bathymetry dynamics in Lake Urmia using extensive field data and high-resolution satellite imagery