Tackling water security: A global need of cross-cutting approaches

Assessing the Efficiency of a Drinking Water Treatment Plant Using Statistical Methods and Quality Indices

This study presents the efficiency of a drinking water treatment plant from Constanța, Romania. Individual and aggregated indices are proposed and built using nine water parameters for this aim. The analysis of individual indices permits the detection of the period of malfunctioning of the water treatment plant with respect to various parameters at various sampling points. In contrast, the cumulated indices indicate the overall performance of the treatment plant during the study period, considering all water parameters. It was shown that the outliers significantly impact the values of some indices. Comparisons between the simple average and weighted average indices (built taking into account the importance of each parameter) better reflect the impact on the water quality of some chemical elements that might harm people's health when improperly removed.

Toward understanding the interaction of shale gas-water-carbon nexus in Sichuan-Chongqing region based on county-level water security evaluation

This study develops a comprehensive framework for understanding the interaction of shale gas-water-carbon nexus in Sichuan-Chongqing region. Within this framework, a county-level water security index (WSI) evaluation system is structured. Spatial autocorrelation model and spatial matching degree model are integrated to illustrate the spatial agglomeration characteristics of water security and the water-carbon relationship, respectively. The impacts of shale gas development on water security and carbon emissions are evaluated based on identification of shale well productivity. Results show that about 25.17% of counties with WSI < 0.4 (unsafe), especially in the eastern region. The central cities (such as Chengdu and Neijiang) should take active steps to reach a safety threshold (WSI ≥ 0.6). Population growth can accelerate water security deterioration through uncertainty analysis. Moreover, the spatial matching degree between WSI and carbon emissions in most cities is extremely poor (< 0.5), implying that these cities should optimize their energy structure and promote green transformation. Water used for shale gas extraction can hardly be ignored from a county-scale perspective, especially in Tongliang, Tongnan, and Jianyang. The future shale gas development would pose a threat to the regional climate.

Hydrochemistry, water quality and health risk assessment of streams in Bismil plain, an important agricultural area in southeast Türkiye

In this study, the water quality of Ambar, Kuruçay, Pamuk and Salat streams, which are the important tributaries of the Tigris River in the Bismil Plain (Diyarbakır, Türkiye) was assessed using 19 physicochemical parameters. Except for a few exceptions, all parameters in the water samples taken from the streams were below the drinking water limit values. Kuruçay Stream had significantly higher TOC, Na+, NO3-, NO2-, Cl- and SO42- levels and lower DO levels than other streams (p < 0.05) due to sewage water discharges, animal manure storage areas near the stream and irrigation return flows. In all streams, Ca-HCO3 was dominant water type. Gibbs diagram indicated that rock weathering is the major factor controlling the hydrochemistry of the streams. According to the results of water quality index (WQI), all sampling stations of Ambar, Pamuk and Salat streams and K1 station of Kuruçay Stream had "good" quality water for drinking purposes, while K2 station of Kuruçay Stream had "poor" quality water. Irrigation indices (permeability index, sodium percentage, magnesium hazard, residual sodium carbonate, Kelley's ratio, sodium adsorption ratio and potential salinity) revealed that all water samples taken from the streams were suitable for irrigation. The water samples from Ambar, Pamuk and Salat streams were in the C2S1 (medium salinity and low alkalinity) category, while the samples from Kuruçay Stream were in the C2S1 and C3S1 (high salinity and low alkalinity) categories. Both hazard quotient and hazard index values of NO3-N, NO2-N and F- for children and adults were found below 1, indicating that adverse health effects are not expected from exposure to these contaminants via water ingestion and dermal contact. The findings of this study showed that the water quality status of Kuruçay Stream is worse as it receives large amounts of irrigation return flows compared to other streams.

Measurement and simulation of irrigation performance in continuous and surge furrow irrigation using WinSRFR and SIRMOD models

The SIRMOD and WinSRFR models were used to model and assess the irrigation performance under continuous and surge irrigation strategies with two furrow lengths of 70 m and 90 m and stream sizes of 0.4 l/s and 0.6 l/s for each length. According to the normalized root mean squared error (NRMSE) and the relative error (RE), WinSRFR had, on average, excellent accuracy in the continuous and surge irrigation for simulating advance-recession times (NRMSE: 6.15 and 4.24% for advance time, and 2.20 and 5.20% for recession time), infiltrated water depth (NRMSE: 3.37 and 6.38%), and runoff volume (RE: 6.93 and 2.57%), respectively. SIRMOD had also, on average, excellent simulation in the continuous and surge irrigation for advance-recession times (NRMSE: 3.34 and 2.45% for advance time, and 2.28 and 6.41% for recession time), infiltrated water depth (NRMSE: 2.98 and 5.27%), and runoff volume (RE: 5.31 and 17.49%), respectively. The average of irrigation application efficiency (AE), distribution uniformity (DU), deep percolation (DP), and tail-water ratio (TWR) were 61.50, 90.25, 11.75, and 26.75% in continuous irrigation, and 72.03, 94.09, 8.39, and 19.57% in surge irrigation, respectively, which shows that surge irrigation increased AE (irrigation management performance) and DU (irrigation method performance) and reduced DP and TWR compared to continuous irrigation. Moreover, longer furrow lengths increased AE and DP under both irrigation methods, while it decreased TWR and DU. However, increasing the stream size decreased AE and DP and increased TWR under both continuous and surge irrigations. The higher stream size improved DU in continuous irrigation but reduced DU in surge irrigation. The results confirmed that both SIRMOD and WinSRFR are reliable analytical tools to evaluate furrow irrigation strategies for improving irrigation management. In conclusion, this study showed that surface irrigation models could be employed in practice by irrigation engineers and practitioners to design and define the optimized furrow length and stream size in arid and semi-arid areas where efficient and high performance irrigation strategies are required to save water and reduce water loss.

Ecological and health risk assessment and quantitative source apportionment of dissolved metals in ponds used for drinking and irrigation purposes

In this study, dissolved metal levels of 10 different ponds used as irrigation and drinking water sources in the north of Saros Bay (Türkiye) were evaluated using multivariate statistical methods, contamination and ecological risk indices, and absolute principal component score-multiple linear regression (APCS-MLR). The mean levels of metals in the ponds ranged from 0.045 µg/L (Cd) to 127 µg/L (Mn). Pond 7 used for drinking water source had the lowest total metal level. Only Mn levels in two ponds (P1 and P2) slightly exceeded the critical value set by EU Drinking Water Directive. However, the levels of all metals in all ponds were lower than the critical values set for irrigation water and aquatic life. According to the heavy metal pollution index (HPI), five ponds showed low metal pollution in terms of drinking water quality, four ponds showed moderate metal pollution, and one pond (P1) showed moderate to heavy pollution. According to the Nemerow pollution index (NPI) values (0.26-1.82), ponds P1 and P2 showed slight metal pollution, while other ponds showed insignificant metal pollution. Contamination degree (CD) values of ponds varied between 0.95 and 3.33, indicating that all ponds showed low pollution. In terms of irrigation water quality, all ponds showed low or insignificant metal pollution according to the HPI, NPI, and CD values. According to the ecological risk index (ERI) values, metals in all ponds posed low ecological risks for both drinking and irrigation purposes. Factor analysis identified two potential sources: mixed sources and natural sources. The APCS-MLR model results revealed that mixed sources and natural sources contributed 78.99% and 21.01% to dissolved metals in the ponds, respectively. Health risk assessment results indicated that both individual and combined metals in the ponds would not cause non-carcinogenic risks to both adults and children. Similarly, it was found that Cr and As would not cause carcinogenic risks to the residents of the region.

Effects of land use and slope on water quality at multi-spatial scales: a case study of the Weihe River Basin

Exploring the impact of land use and slope on basin water quality can effectively contribute to the protection of the latter at the landscape level. This research concentrates on the Weihe River Basin (WRB). Water samples were collected from 40 sites within the WRB in April and October 2021. A quantitative analysis of the relationship between integrated landscape pattern (land use type, landscape configuration, slope) and basin water quality at the sub-basin, riparian zone, and river scales was conducted based on multiple linear regression analysis (MLR) and redundancy analysis (RDA). The correlation between water quality variables and land use was higher in the dry season than in the wet season. The riparian scale was the best spatial scale model to explain the relationship between land use and water quality. Agricultural and urban lands had a strong correlation with water quality, which was most affected by land use area and morphological indicators. In addition, the greater the area and aggregation of forest land and grassland, the better the water quality, while urban land presented larger areas with poorer water quality. The influence of steeper slopes on water quality was more remarkable than that of plains at the sub-basin scale, while the impact of flatter areas was greater at the riparian zone scale. The results indicated the importance of multiple time-space scales to reveal the complex relationship between land use and water quality. We suggest that watershed water quality management should focus on multi-scale landscape planning measures.

Evaluation of the water quality of a highly polluted stream with water quality indices and health risk assessment methods

The water quality of Çorlu Stream, located in the Thrace region of Türkiye, and exposed to intense industrial pressure, was evaluated by monitoring 10 toxic metals and 13 other water quality variables in the dry and wet seasons of 2021. Seven different water quality indices were applied to determine the pollution level at the sampling stations in the stream. In addition, human health risks from exposure to toxic metals in stream water via ingestion and dermal contact were evaluated. The results showed that the water quality at stations S2 and S3 of Çorlu Stream receiving domestic and industrial discharges are seriously polluted by NH4-N, PO4-P, COD, BOD5 and suspended solids according to surface water quality standards. In addition, these stations were highly polluted and had poor water quality according to the results of the water quality indices. The average Cr level at station S3 exceeded the permissible levels set for the protection of aquatic life due to effluent discharges from the leather factories. Considering the results of the health risk assessment methods, non-carcinogenic risks from ingestion of combined metals in stream water can be expected at station S3 for both children and adults and at station S2 for children. Also, it was estimated that Cr and As at station S3 may cause carcinogenic health risks for residents.

Water quality assessment of the Karasu River (Turkey) using various indices, multivariate statistics and APCS-MLR model

Determining the water quality status of a river and accurately identifying potential pollution sources threatening the river are pillars in effective control of pollution and sustainable water management. In this study, water quality indices, multivariate statistics and absolute principal component score-multiple linear regression (APCS-MLR) were applied to evaluate the water quality of the Karasu River, the main tributary of the Euphrates River (Turkey). For this, 19 water quality variables were monitored monthly at eight stations along the river during one year. Based on the mean dissolved oxygen (DO), electrical conductivity (EC), nitrate-nitrogen (NO₃-N), orthophosphate-phosphorus (PO₄-P), total phosphorus (TP), ammonium-nitrogen (NH4-N), chemical oxygen demand (COD) and total nitrogen (TN) levels, most stations of the river had "very good" water status according to surface water quality criteria. Spatial cluster analysis (CA) divided eight stations into three regions as clean region, moderate clean region and very clean region. The mean values of Nutrient Pollution Index indicated that the river was "no polluted". Similarly, Water Quality Index and Organic Pollution Index values indicated that the river water quality was between "good" and "excellent". A minimum water quality index (WQI_min) consisted of ten crucial parameters was not significantly different with the WQI based on all the 17 parameters. Discriminant analysis (DA) results showed that water temperature (WT), EC, chlorophyll-a (Chl-a), potassium (K), calcium (Ca), NO₃-N and COD are the variables responsible for temporal changes, while WT, total dissolves solids (TDS), Chl-a, K, magnesium (Mg), Ca, NH₄-N and COD are the variables responsible for spatial changes in the river water quality. Principal component analysis/factor analysis (PCA/FA) identified four potential sources, including anthropogenic, natural, seasonal and phytoplankton. Source apportionment in the APCS-MLR model revealed that seasonal and anthropogenic sources contributed 35.2% and 25.5% to river water quality parameters, respectively, followed by phytoplankton (21.4%) and natural sources (17.9%).