Seasonal Water Quality Research Articles

Seasonal water quality trends in a tailwater recovery system in the Mississippi Delta

In the Mississippi Delta region, tailwater recovery (TWR) systems are an important best management practice to address both water quality and quantity issues. TWRs are surface water capture-and-irrigation reuse systems using a combination of a ditch to capture surface water, an on-farm storage (OFS) reservoir to store captured surface water, and pumps to move surface water from the ditch into the OFS reservoir and to irrigate nearby fields. To determine if TWR systems are an effective way to reduce water use and downstream nutrient loads, water quality and quantity data from a ditch and pond TWR system in Sunflower County, Mississippi, were measured for five years. Objectives of this study were to assess seasonal TWR system runoff and runoff water quality trends. All water quality parameters had clear seasonal variation, except for chlorophyll <i>a</i>. Dissolved oxygen (DO), solids, conductivity, total dissolved organic carbon (TDOC), total phosphorus (TP), and total Kjeldahl nitrogen (TKN) exhibited significant differences between OFS reservoir and ditch sites. Total solids were 2 to 4 times higher in the ditch than in the reservoir, depending on the season, indicating sediment lost from fields through runoff is not necessarily returned to the fields via irrigation from the reservoir. Nutrients were also generally higher in the ditch than in the reservoir. Phosphate (PO₄) was 1.4 times higher in the ditch in spring compared to the reservoir, while ammonium (NH₄) and nitrate (NO₃) were 2 to 4 times higher in the ditch during the summer. These results suggest the reservoir serves an important function to process nutrients and sediments through settling, biological uptake of nutrients, and biogeochemical transformations and emphasizes the importance of a closed TWR system.

Assessment of Surface Water Quality of Huai Luang River in Udon Thani, Thailand, Using the Water Quality Index

This study aimed to analyze the surface water quality of the Huai Luang River using the water quality index (WQI) method. Five parameters were analyzed to assess the water quality of the Huai Luang River; they were dissolved oxygen (DO), biochemical oxygen demand (BOD), total coliform bacteria (TCB), fecal coliform bacteria (FCB), and ammonia (NH3). The Huai Luang River is the municipality’s primary consumption water source in Udon Thani province, Thailand. WQI classifications were calculated by using the surface water quality standards program of Thailand’s Pollution Control Department (PCD-WQI). The results showed that the water quality in the Huai Luang River was bad status, in the WQI range of 54-60 scores. The major sources of pollutants in the Huai Luang River were wastewater from communities, agriculture, and animal farms are the main contributors to water pollution. Seasonal water quality variations were observed at each monitoring site from March 2022 to February 2023. WQI concentration in the rainy season (March to June) was generally among the highest (57 score) compared with other seasons (56 score in winter and 54 score in summer). While the WQI concentration of the upstream sampling site (domestic wastewater) had the lowest (55 score) compared with the other sites (59 score for midstream and 60 score for downstream). Therefore, this research study presented valuable information on WQI for the Huai Luang River for water quality management by administrators and local community participation.

Development of Canadian Water Quality Index (WQI) of Vidhyadhari, an Estuarine River in Eastern India

Surface water represents one of the most utilized sources for water distribution systems globally, despite the fact that rapid urbanization and industrialization has reduced its cleanliness. As a result, the end-user's health is seriously impacted by the dirty water. Nevertheless, it is clear that many developing nations, including India, pay little regard to or care about this crucial issue. The Vidhyadhari River has become a receiver of high organic and bacteriological load of entire Kolkata City through Basanti canal. As a result, the purpose of this investigation is to evaluate how rapid urbanization and industrialization has changed the water quality of Vidhyadhari River using Canadian Water Quality Index (WQI). We have used seasonal water quality data collected at two monitoring stations (Haroa bridge and Malancha) from 2011 to 2020 to study the water quality of Vidhyadhari River. Results of the study indicated that the annual WQI value of Haroa brigde ranged between 21.62 (very bad) and 62.89 (medium) with an average of 27.29 (bad), whereas annual WQI value of Malancha station ranged between 15.44 (very bad) and 43.09 (bad) with an average of 18.77 (very bad). In comparison to downward location, the water quality of Vidhyadhari River was somehow good at upstream i.e., Haroa brigde. According to WQI, the water quality of Vidhyadhari River fall into bad to very bad category, which indicated deterioration of river water quality. Factor analysis revealed that both stations are predominated by hardness cluster (hardness, calcium, magnesium and chloride) followed by cluster of total dissolved solids (TDS), sulphate and ammonia. Sewer, excessive human activity, industrial discharges, poor sanitation, and urban runoff outflow can be extrapolated as the main causes for the deterioration of Vidhyadhari River water quality. This study emphasized the significance of implementing measurement actions, introduction of watershed characteristics and implications for developing water management strategies.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Seasonal Water Quality Changes and the Eutrophication of Lake Yilong in Southwest China

To better understand the seasonal variation characteristics and trend of water quality in Lake Yilong, we monitored water quality parameters and measured nutrients, including the water temperature (WT), Chlorophyll-a (Chl-a), dissolved oxygen (DO) and pH from September 2016 to May 2020, total nitrogen (TN) and total phosphorus (TP) from October 2016 to August 2018. The results showed that the lake water was well mixed, resulting in no significant thermal stratification. The DO content was decreased in the northwest part of the lake during September and October, resulting in a hypoxic condition. It also varied at different locations of the lake and showed a high heterogeneity and seasonal variability. The Chl-a concentration in Lake Yilong demonstrated seasonal and spatial changes. It was maximum at the center and southwest area of the lake in January. However, in the northwest part of the lake, the maximum value appeared in September and October. The content of TN in the rainy season increased by 75% compared with that in dry season and TP content show a downward trend (from 0.11 mg/L to 0.05 mg/L). The comprehensive nutrition index evaluation shows that the water quality of Lake Yilong in 2016 was middle eutrophic (TLI = 60.56), and that in 2017 (TLI = 56.05) and 2018 (TLI = 56.38) was weak eutrophic, showing that the nutritional status has improved. TN remained at a high level (2.15 ± 0.48 mg/L), water quality needs further improvement. Based on our monitoring and analysis, it is recommended that human activities in the watershed of the lake should be constrained and managed carefully to maintain the water quality of the lake and adopt effective water quality protection and ecological restoration strategies and measures to promote continuous improvement of water quality, for a sustainable social development.

Impacts of land uses on spatio-temporal variations of seasonal water quality in a regulated river basin, Huai River, China

Land use impacts from agriculture, industrialization, and human population should be considered in surface water quality management. In this study, we utilized an integrated statistical analysis approach mainly including a seasonal Mann-Kendall test, clustering analysis, self-organizing map, Boruta algorithm, and positive matrix factorization to the assessment of the interactions between land use types and water quality in a typical catchment in the Huai River Basin, China, over seven years (2012–2019). Spatially, water quality was clustered into three groups: upstream, midstream, and downstream/mainstream areas. The water quality of upstream sites was better than of mid-, down-, and mainstream. Temporally, water quality did not change significantly during the study period. However, the temporal variation in water quality of up-, down-, and mainstream areas was more stable than in the midstream. The interactions between land use types and water quality parameters at the sub-basin scale varied with seasons. Increasing forest/grassland areas could substantially improve the water quality during the wet season, while nutrients such as phosphorus from cropland and developed land was a driver for water quality deterioration in the dry season. Water area was not a significant factor influencing the variations of ammonia nitrogen (NH3-N) and total phosphorus (TP) in the wet or dry season, due to the intensive dams and sluices in study area. The parameters TP, and total nitrogen (TN) were principally linked with agricultural sources in the wet and dry seasons. The parameters NH3-N in the dry season, and chemical oxygen demand (CODCr) in the wet season were mainly associated with point source discharges. Agricultural source, and urban point source discharges were the main causes of water quality deterioration in the study area. Collectively, these results highlighted the impacts of land use types on variations of water quality parameters in the regulated basin.

Evaluation of impacts of environmental factors and land use on seasonal surface water quality in arid and humid regions using structural equation models

Understanding of the buffer scale effect on water quality changes analysis in arid and humid regions is of great significance for exploring the best scale for water quality pollution and scientific planning of land use. The objective of this study is to determine the optimal buffer scales (500, 1000, 1500, 2000, 2500 and 3000 m) of land use that affect ammonia nitrogen (NH3-N) and total phosphorus (TP) in the Jing-Bortala River Watershed (JBRW) (arid region) and the Liyang Region (LR) (humid region) under a site buffer. PLS-SEM was used to fit the pathway relationships between the influencing factors and water quality to investigate the driving factors of NH3-N and TP in different seasons. The results showed that: (1) seasonal fluctuations in NH3-N and TP concentrations were found in both the arid and humid regions, with the arid region having higher values than humid region; the coefficient of variation (CV) of NH3-N and TP was higher in arid and humid region, and the CV of NH3-N and TP were higher in spring and autumn in arid region than that in spring and autumn in humid region; (2) the 2500 m (0.262 ≤ R2 ≤ 0.633) buffer is the optimal scale for studying NH3-N and TP in arid region, whereas the 2000 m (0.262 ≤ R2 ≤ 0.686) scale works well in humid region; and (3) farmland (NDVI) was the largest influencing factor for NH3-N and TP changes in arid region, accounting for 28.95 % of the average percent total impacts. Furthermore, water area (NDWI) was the predominant influencing factor in humid region, occupying 33.93 % of the average percent total impacts. The influence of land use type (indices) on surface water quality is greater than that of environmental factors. Thus, these new insights into an appropriate buffer scale can be used as a guide for water pollution management in arid and humid environments.

UV disinfection audit of water resource recovery facilities identifies system and matrix limitations

The use of ultraviolet (UV) light as a disinfectant in water resource recovery facilities is a well-accepted and increasingly popular disinfection option. Different assessment techniques, such as collimated beam testing, biodosimetry, fluorescent microspheres, and computational fluid dynamic modelling, exist to evaluate suitability and validate fluence of full-scale UV systems; however, each of these techniques has limitations. UV auditing overcomes these limitations by concurrently estimating the minimum fluence required to meet effluent discharge limits, providing direct inactivation results of the regulated organism, and estimating the minimum fluence achieved by an installed full-scale system. Four wastewater facilities with various treatment technologies and flowrates were selected to be audited. Bench-scale collimated beam performance fluence-response curves were developed for E. coli and the modeled data was compared to plant performance to determine system versus matrix limitations. The results found that UV auditing successfully identified system and matrix limitations for each of four different wastewater treatment facilities. Furthermore, seasonal differences between two sampling locations were confirmed via UV auditing. Seasonal water quality analysis of WWTF-C resulted in a more challenging wastewater matrix to treat with increasing influent E. coli during the Fall. The UV audit identified that WWTF-C was undersized and limited in its capacity. In summary, UV auditing provides a clear and robust method to better understand how wastewater treatment facilities perform and provides a novel approach to determine the fluence of an installed full-scale reactor.

Influence of Land Use and Land Cover Patterns on Water Quality at Different Spatio-temporal Scales in Hehuang Valley

Based on the measured water quality data of Huangyuan County, Huzhu Tu Autonomous County, and Minhe Hui Tu Autonomous County in Hehuang Valley of Qinghai province in the normal and wet seasons, the effects of land use and land cover patterns on regional seasonal water quality were analyzed using remote sensing technology and mathematical statistics. The results showed that:① the concentrations of total nitrogen and total phosphorus in the surface water of Hehuang Valley were high. Water pollution areas (Class Ⅳ and Ⅴ) were mainly concentrated in the lower reaches of the river and the junction of tributaries. ② The explanation rate of land use to water quality in the normal season was higher than that in the wet season. The optimal scale was the 200 m buffer scale in the normal season, and farmland and towns were the main influencing factors. The optimal scale in the wet season was the 5 km buffer scale, and the main influencing factor was the forest. ③ In the normal season, the proportion of farmland was positively correlated with the concentration of total nitrogen and permanganate index but negatively correlated with the concentration of total phosphorus. The proportion of town area was positively correlated with the water quality index. The proportion of grassland area in the wet season was positively correlated with the permanganate index. The proportion of forestland area was negatively correlated with water quality index in both periods. Farmland, grassland, and town areas were the "source" landscape of pollutants, but farmland also played a role in intercepting pollutants to a certain extent. Forest land was the "sink" landscape of pollutants. ④ The pattern of forestland in the 200 m buffer zone in the normal season had a high explanatory rate for water quality, and the largest patch index (LPI) and patch density (PD) were the main factors. The study showed that it is an important measure to purify the surface water quality of Hehuang Valley by rationally planning the proportion of residential land and cultivated land and improving the coverage rate and aggregation degree of forestland around the riparian zone.

Stream Distance-Based Geographically Weighted Regression for Exploring Watershed Characteristics and Water Quality Relationships

We developed a novel spatial stream network geographically weighted regression (SSN-GWR) by incorporating stream-distance metrics into GWR. The model was tested for predicting seasonal total nitrogen (TN) and total suspended solids (TSS) concentrations in relation to watershed characteristics for 108 sites in the Han River Basin, South Korea. The SSN-GWR model was run with the average seasonal water quality parameters from 2012 through 2016 and was validated with the data from 2017 through 2021. The model fit among ordinary least square regression, standard GWR (STD-GWR), and stream distance weighted SSN-GWR were compared based on their ability to explain the variation of seasonal water quality parameters. We also compared residual spatial autocorrelations as well as various error parameters from these models. Compared to the STD-GWR model, the SSN-GWR model generally provided better model fit, reduced residual spatial autocorrelation, and lessened overall modeling errors. Results show that the spatial patterns of model fit, as well as various coefficients from the upstream distance weighted regressions, capture local patterns as a product of upstream–downstream relations. We demonstrate that a successful model could be developed by integrating stream distance into the GWR, which not only improves model fit but also reveals realistic hydrological processes that relate watershed characteristics to water quality along with the stream network. The local variations in model fit derived from this work can be used to devise fine-scale interventions for water quality improvements in a spatially heterogeneous complex river basin.

Remote Estimation of Water Clarity and Suspended Particulate Matter in Qinghai Lake from 2001 to 2020 Using MODIS Images

Climate change and human activities have been heavily affecting oceanic and inland waters, and it is critical to have a comprehensive understanding of the aquatic optical properties of lakes. Since many key watercolor parameters of Qinghai Lake are not yet available, this paper aims to study the spatial and temporal variations of the water clarity (i.e., Secchi-disk depth, ZSD) and suspended particulate matter concentration (CSPM) in Qinghai Lake from 2001 to 2020 using MODIS images. First, the four atmospheric correction models, including the NIR–SWIR, MUMM, POLYMER, and C2RCC were tested. The NIR–SWIR with decent accuracy in all bands was chosen for the experiment. Then, four existing models for ZSD and six models for CSPM were evaluated. Two semi-analytical models proposed by Lee (2015) and Jiang (2021) were selected for ZSD (R2 = 0.74) and CSPM (R2 = 0.73), respectively. Finally, the distribution and variation of the ZSD and CSPM were derived over the past 20 years. Overall, the water of Qinghai Lake is quite clear: the monthly mean ZSD is 5.34 ± 1.33 m, and CSPM is 2.05 ± 1.22 mg/L. Further analytical results reveal that the ZSD and CSPM are highly correlated, and the relationship can be formulated with ZSD=8.072e−0.212CSPM (R2 = 0.65). Moreover, turbid water mainly exists along the edge of Qinghai Lake, especially on the northwestern and northeastern shores. The variation in the lakeshore exhibits some irregularity, while the main area of the lake experiences mild water quality deterioration. Statistically, 81.67% of the total area is dominated by constantly increased CSPM, and the area with decreased CSPM occupies 4.56%. There has been distinct seasonal water quality deterioration in the non-frozen period (from May to October). The water quality broadly deteriorated from 2001 to 2008. The year 2008 witnessed a sudden distinct improvement, and after that, the water quality experienced an extremely inconspicuous degradation. This study can fill the gap regarding the long-time monitoring of water clarity and total suspended matter in Qinghai Lake and is expected to provide a scientific reference for the protection and management of the lake.

Spatial and Seasonal Drinking Water Quality Assessment in a Sub-Saharan Country (Guinea-Bissau)

The United Nations Sustainable Development Goal target 6.1 calls for universal and equitable access to safe and affordable drinking water. Worldwide, about 2.2 billion people live without access to safe water, and millions of people suffer from waterborne pathogens each year, representing the most pressing situation in developing countries. The aim of this study was to investigate the drinking water quality dynamics across an endemic cholera sub-Saharan country (Guinea-Bissau), and understand its implications for public health. Microbiological and physical–chemical quality parameters of 252 major water sources spread all over the country were seasonally surveyed. These comprised hand-dug shallow wells and boreholes, fitted with a bucket or a pump to retrieve water. The results showed that the majority of water sources available to the population were grossly polluted with faecal material (80%), being unsuitable for consumption, with significantly (p &lt; 0.05) higher levels during the wet season. Hand-dug wells revealed the highest contamination levels. The chemical contamination was less relevant, although 83% of the water sources were acidic (pH &lt; 6.5). This study highlights the potential health risk associated with the lack of potable drinking water, reinforcing the evidence for water monitoring, and the need to improve WASH (water, sanitation, and hygiene) infrastructure and water management in West African countries. In addition, the authors suggest easy-to-implement interventions that can have a dramatic impact in the water quality, assisting to reduce the associated waterborne diseases rise.

Seasonal forecasting of lake water quality and algal bloom risk using a continuous Gaussian Bayesian network

Abstract. Freshwater management is challenging, and advance warning that poor water quality was likely, a season ahead, could allow for preventative measures to be put in place. To this end, we developed a Bayesian network (BN) for seasonal lake water quality prediction. BNs have become popular in recent years, but the vast majority are discrete. Here, we developed a Gaussian Bayesian network (GBN), a simple class of continuous BN. The aim was to forecast, in spring, mean total phosphorus (TP) and chlorophyll a (chl a) concentration, mean water colour, and maximum cyanobacteria biovolume for the upcoming growing season (May–October) in Vansjø, a shallow nutrient-rich lake in southeastern Norway. To develop the model, we first identified controls on interannual variability in seasonally aggregated water quality. These variables were then included in a GBN, and conditional probability densities were fit using observations (≤39 years). GBN predictions had R2 values of 0.37 (chl a) to 0.75 (colour) and classification errors of 32 % (TP) to 17 % (cyanobacteria). For all but lake colour, including weather variables did not improve the predictive performance (assessed through cross-validation). Overall, we found the GBN approach to be well suited to seasonal water quality forecasting. It was straightforward to produce probabilistic predictions, including the probability of exceeding management-relevant thresholds. The GBN could be sensibly parameterised using only the observed data, despite the small dataset. Developing a comparable discrete BN was much more subjective and time-consuming. Although low interannual variability and high temporal autocorrelation in the study lake meant the GBN performed only slightly better than a seasonal naïve forecast (where the forecasted value is simply the value observed the previous growing season), we believe that the forecasting approach presented here could be particularly useful in areas with higher sensitivity to catchment nutrient delivery and seasonal climate and for forecasting at shorter (daily or monthly) timescales. Despite the parametric constraints of GBNs, their simplicity, together with the relative accessibility of BN software with GBN handling, means they are a good first choice for BN development with continuous variables.

Effects of multi-scale landscape pattern changes on seasonal water quality: a case study of the Tumen River Basin in China.

Landscape patterns affect river water quality by influencing hydrological processes. However, with changes in spatial scale and season, landscape factors may have different effects on water pollution. Therefore, quantitative analysis of the scale effect of each landscape index was carried out to determine the mutation point of river water quality and its index relationship, which is of great significance to landscape planning and water quality protection. Based on the water quality monitoring data of 19 sampling points in the Tumen River Basin, we used redundant methods to quantify the spatial scale effects and seasonal dependencies of various landscape indicators on river water quality, then determined the mutation point of the water quality along the landscape-scale gradient. The results showed that different types of landscape indicators have different effects on river water quality, and the spatial-scale effect of landscape composition affects a river's water quality, while landscape configuration indicators had the highest sensitivity. The landscape characteristics of river straps better explained the overall water quality, a phenomenon that is more obvious in the wet season than the dry season. We identified a key landscape indicator of urban area proportion (Urban%) and a contagion index (CONTAG) as the river strap scale. An Urban% < 30% and a CONTAG > 70% suggest effective landscape planning parameters that effectively protect water quality. The results indicated that, to protect water quality, landscape regulation should follow scale-adaptability measures and consider landscape thresholds, which cause abrupt changes in water quality.

Evaluation of Seasonal Water Quality of Drinking Water in Six Residential Estates across Ogun State in Nigeria

The use of water to satisfy human without any health risk necessitates the need for assessment of potable water quality for human consumption. Water samples were collected across six selected housing estates for two consecutive dry and wet seasons within Ogun State, and their parameters such as TDS, EC, Mn, Zn, Cd, Pb and Ni were analysed for quality assessment. On spot analysis was carried out for the in-situ parameters using HANNAH water kit. The water samples were digested in triplicates for each estate, and analysed with AAS for the selected heavy metals (HMs). The obtained data were subjected to descriptive and inferential statistics, and the obtained values were compared with WHO, NIS and NESREA standards to ascertain the water quality and potability. Concentrations (mg/ L) of the analysed parameters ranged as TDS: 56.00 ± 10.44 to 162.07 ± 9.81, Cd: 0.01 ± 0.00 to 0.16 ± 0.10, Pb: 0.16 ± 0.02 to 1.69 ± 0.10, Fe: 0.04 ± 0.04 to 4.75 ± 0.21, and Ni: 0.04 ± 0.02 to 0.85 ± 0.04. The EC (µS/ cm) ranged from 42.82 ± 10.59 to 499.12 ± 31.20. The water quality showed seasonal variations, more polluted in the wet season than dry season, which can be attributed to storage tanks, piping systems and runoff from drainages, residential wastes, and the neighbouring small scale industrial activities. The research suggests water treatment for the consumers to get safe water of potable quality.

Passive Treatment of Circumneutral Mine Drainage from the St. Louis Mine Tunnel, Rico CO: Part 3—Horizontal Wetlands Treatment Train Pilot Study

AbstractMine drainage from the St Louis Tunnel (located at the Rico-Argentine Site) is circumneutral most of the year, with spring freshets increasing flow, decreasing pH and increasing metals concentrations. This study was designed to test the performance of a demonstration-scale horizontal wetlands passive treatment train, comprised of a settling basin, surface flow wetland, horizontal-flow anaerobic wetland, aeration channel, and rock drain, during two years of influent water chemistry at a constant 113 L/min (30 gpm) flow rate. Total Zn, Cd, and Mn effluent concentrations met project treatment goals (PTGs) 75, 96.9, and 100% of the time, respectively, and 93.9, 100, and 100% of the time for the dissolved metals. Most PTG exceedances occurred during the freshet events. Most Zn and Cd attenuation was attributed to sulfide precipitation in the anaerobic cell and capture/filtration of suspended ZnS particles in the anaerobic wetland and rock drain. Manganese was attenuated in the aerobic portion of the anaerobic cell (influent transition zone) as Mn oxides and carbonates. Oxidation of Mn occurred in the rock drain as biogenically formed Mn oxides adhered to the rock matrix. Carryover of dissolved sulfides from the anaerobic cell limited the rock drain’s Mn removal efficiency. Low temperatures did not significantly affect biological activity within the system; the effects of seasonal water quality were more important.

Seasonal and Spatial Water Quality of Awash River for Irrigation at Dubti/Tendaho, North Eastern Ethiopia

Salt affected soils are common in the irrigated arid and semi arid regions where irrigation with poor quality water is a common practice. In all irrigation farms, particularly at Dubti/Tendaho state farm, clear information on Awash River water quality for irrigation is lacking. Therefore, this study was conducted at Dubti/Tendaho state farm to investigate seasonal and spatial variations of irrigation water quality in Awash River. Water samples were collected from four sampling sites (dam to field) in monthly interval from September 2013 to August 2014. Relevant data were collected and interpreted as per the irrigation water quality guidelines. The result showed that pH, electrical conductivity (EC), sodium adsorption ratio (SAR) and adjusted sodium adsorption ratio (adj.SAR) were beyond the permissible limit in Autumn and Summer. The residual sodium carbonate (RSC) and bicarbonate (HCO 3 - ) were unsuitable in all seasons except in Spring. Sodium percentage (Na %) was permissible in Winter and Spring whereas doubtful in Autumn and unsuitable in Summer seasons. Sodium toxicity was severe in Summer and Autumn (&gt;9 meq l -1 SAR) while slight to moderate in Winter and Spring (3 - 9 meq l -1 SAR) seasons. However, chloride (Cl - ) hazard was safe (&lt; 4 meq l -1 ) in all seasons except Summer which showed slight to moderate. Spatially, an increasing trend on Cl - , pH and Na% from the dam to the end of field drain water(FDW) whereas a decreasing trend on EC, Na, Mg, Ca, K, HCO 3 - , total dissolved solids (TDS), SAR, and RSC were observed. The results revealed that irrigation water quality was highly saline and toxic in Summer and Autumn whereas slight to safe in Winter and Spring seasons. Hence, it is possible to infer that the planting date of crops should be adjusted in Winter and Spring seasons when the quality of irrigation water becomes safe. Keywords: Awash River, irrigation water quality , Electrical conductivity, pH, residual sodium carbonate, sodium adsorption ratio , toxicity, water quality parameters DOI: 10.7176/JRDM/85-02 Publication date: May 31 st 2022

Impact of land-use/land-cover and landscape pattern on seasonal in-stream water quality in small watersheds

Changes in land use land cover (LULC) and landscape pattern in arid areas can considerably impact water quality in small watersheds. Exploring the associations between land use, landscape pattern, and riverine water quality can inform land-use planning for water-quality security. In northwest China's Jing River Watershed (JRW), water samples were collected at 67 points in 2016–2017 and analyzed. Coupled with Sentinel-2 remote-sensing images, this study calculated the Canadian Water Quality Index (CWQI) to assign the water-quality category. The Random Forest classification characterized current LULC patterns and computed landscape metrics in a riparian buffer zone. The stepwise multiple linear regression and redundancy analysis methods investigated the relationships amongst LULC, eight landscape metrics, and eight water-quality parameters. The results indicated high concentrations of total phosphorus (TP) and total nitrogen (TN) in the JRW's middle and lower reaches. For CWQI, lacking evident temporal fluctuations was contrasted by noticeable spatial variations. Intense Human activities have aggravated the deterioration of the water quality of the JRW. LULC-type changes, including Waterbody, Forest-grassland, and Farmland, imposed notable impacts on seasonal water quality. For landscape metrics, patch cohesion index (COHESION) strongly correlated with chemical oxygen demand (COD), mineralization degree (MD), and TN. By contrast, patch density (PD) correlated negatively with TN. Interspersion juxtaposition index (IJI) strongly correlated with biochemical oxygen demand after five days (BOD5). COHESION, PD, and IJI can be critical factors in predicting water-quality changes at the small-watershed scale. Our findings offered a robust scientific basis to refine regional sustainable water development strategy and rational water-resource management.

Impacts of land use and landscape pattern on water quality at multiple spatial scales in a subtropical large river

AbstractThe coupling between land use/landscape pattern and water quality in river systems varies across different spatial and temporal scales. It is important to understand the association between water quality and land use/landscape pattern across different spatial and temporal scales for the protection of water resources. Here, we measured seasonal water quality at 12 sub‐basins in the upper reaches of the Han River (UHR) between 2010 and 2018. We conducted factor analysis and redundancy analysis to determine the links between land use and water quality at multiple spatial scales and to identify the main factors influencing water quality. We found that the concentration of nutrients, including total nitrogen, total phosphorus, nitrate‐N and ammonium‐N, was higher during the wet season than the dry season. Total nitrogen was the main driver of nutrient pollution in the UHR, whereas total phosphorus was identified as another potential nutrient pollutant. We also found that water quality parameters were more strongly related to land use types during the wet season than the dry season. Croplands and urban lands increased phosphorus concentrations of river water, whereas forest and grasslands decreased the nitrogen concentrations of river water at the sub‐basin scale. Land use at the riparian zone scales better explained variations in water quality than land use at sub‐basin scales. The explained variations in landscape metrics were generally higher during the dry season than the wet season. The largest patch index and Shannon's diversity index were the main predictors of river water quality in the UHR.

Seasonal atmospheric water harvesting yield and water quality using electric-powered desiccant and compressor dehumidifiers

Atmospheric water harvesting (AWH) is an emerging technology for decentralized water supply and is proving to be viable for use in emergencies, military deployment, and sustainable industries. The atmosphere is a freshwater reservoir that contains 12,900 km3 of water, 6-fold more than the volume of global rivers. Dehumidification water harvesting technologies can be powered by solar, wind, or electric sources. Compressor/refrigerant-based dehumidifiers operate via dew point condensation and provide a cold surface upon which water vapor can condense. Conversely, desiccant-based technologies saturate water vapor using a sorbent that is then heated, and the supersaturated water vapor condenses on a surface when interacting with cooler ambient process air. This work compares productivity, energy consumption, efficiency, cost and quality of water produced of two water-harvesting mechanisms. Electric-powered compressor and desiccant dehumidifiers were operated outdoors for more than one year in the arid southwestern USA, where temperatures ranged from 3.1 to 43.7 °C and relative humidity (RH) ranged from 6 to 85%. The compressor system harvested >2-fold more water than the desiccant system when average RH during the run cycle was >30%, average temperature was >20 °C, and average dew point temperature was >5 °C. Desiccant systems performed more favorably when average RH during the run cycle was <30%, average temperature was <20 °C, and average dew point temperature was <5 °C. Water collected by compressor-based technologies had conductivity up to 180 μS/cm, turbidity up to 190 NTU, and aluminum, iron and manganese near or above the US EPA secondary drinking water standard. Dissolved organic carbon (DOC) averaged <2 mg C/L but ranged up to 12 mg C/L. Water collected by desiccant-based technologies had significantly lower conductivity, metals, and turbidity, and DOC was always <6 mg/L. Aldehydes such as formaldehyde and acetaldehyde and carboxylic acids such as formic acid and acetic acid were primary contributors to DOC. The differences in harvested water quality were attributed to differences in the condensation method between compressor and desiccant AWH technologies. Multiple strategies could be employed to prevent these volatile organic compounds (VOCs) from contributing to DOC in harvested water, such as pretreating air to remove VOCs or post-treating DOC in harvested liquid water.