Investigating water-land-climate interactions is critical for urban development and watershed management. This study examined this nexus by elasticity and statistical approaches through the lens of three watersheds: The Yukon, Mekong and Murray. Here, this study reports the fundamental characteristics, explanations and ecological and management implications of terrestrial determinant influence on the response of water quality to climate drivers. The stability of the response, measured by climate elasticity of water quality (CEWQ), is highly dependent on terrestrial determinants, with strong impacts from anthropogenic biomes and low impacts from surficial geology. Compared to temperature elasticity, precipitation elasticity of water quality is more unstable due to its possible linkages with many terrestrial determinants. Correlation and linear models were developed for the interaction system, which uncovered many interesting scenarios. The results implied that watersheds with a higher ratio of rangeland biomes have a lower risk of instability as compared to watersheds with a higher proportion of dense settlement, cropland and forested biomes. This study discusses some of the most essential pathways where instability might adversely affect CEWQ parameters and recommends suggestions for policy makers to alleviate the instability impacts to bring sustainability to the water environment.

Identification of nonpoint source (NPS) pollution is essential for effective water management. In this study we used a combined approach of hierarchal cluster analysis (HCA) and positive matrix factorization (PMF) to identify NPS pollution for Huaihe River basin in China. NH 3-N, COD, DO and pH were regularly monitored weekly over 2 years (2011-2012) from 27 monitoring stations subjected to high anthropogenic and natural changes. As identified by multiple correspondence analyses, the monitoring stations #3, #9 and #21 are located away from the rest of sites. HCA classified all the stations into 4 groups. PMF identified four factors on each group and each season. They were associated with the major causes of Huaihe River water quality deterioration resulted by discharges inputs from urban, agricultural and industrial land uses. Seasonal NPS pollution variation was found, and it is possibly linked with natural processes, for instance hydrological regime. This research work demonstrates the usefulness of PMF model for the identification of NPS pollution in surface waters. Furthermore, our study also shows that urban, agricultural and industrial land uses were the main factors impairing surface water quality, and limiting NPS pollution would be critical for enhancing surface water quality in the study area.

Investigating the effects of climate and land-use changes on surface runoff is critical for water resources management. The majority of studies focused on projected climate change effects on surface runoff, while neglecting future land-use change. Therefore, the main aim of this article is to discriminate the impacts of projected climate and land-use changes on surface runoff using the Soil and Water Assessment Tool (SWAT) through the lens of the Upper Indus Basin, Pakistan. Future scenarios of the land-use and climate changes are predicted using cellular automata artificial neural network and four bias-corrected general circulation models, respectively. The historical record (2000–2013) was divided into the calibration period (2000–2008) and the validation period (2009–2013). The simulated results demonstrated that the SWAT model performed well. The results obtained from 2000 to 2013 show that climate change (61.61%) has a higher influence on river runoff than land-use change (38.39%). Both climate and land-use changes are predicted to increase future runoff depth in this basin. The influence of climate change (12.76–25.92%) is greater than land-use change (0.37–1.1%). Global weather data has good applicability for simulating hydrological responses in the region where conventional gauges are unavailable. The study discusses that both climate and land-use changes impact runoff depth and concluded some suggestions for water resources managers to bring water environment sustainability.

Impacts of climate change on streamflow have long been an issue of concern for water experts. The main aim of this study is to assess the response of streamflow to precipitation and air temperature. In this study elasticity model was used to compute the precipitation and air temperature elasticity of 6 major rivers in Khyber-Pakhtunkhwa (KP) Province, Pakistan. In contrast to temperature elasticity estimator, box plots of precipitation elasticity estimator have low range and standard deviation leading to greater central affinity which produces valid, appropriate, and statistically significant elasticity results. Precipitation is positively correlated with streamflow while the air temperature is both positively and negatively linked with streamflow. 10% variation in precipitation and air temperature produces 12 to 20% and 8 to 18% change in streamflow, respectively. The sensitivity of streamflow to air temperature is higher as compared to precipitation. This research work shows that precipitation elasticity results are statistically valid and realistic as compared to temperature elasticity results. Moreover, it is suggested to support elasticity results by statistical correlation to avoid misleading and unrealistic results. Results of the current study can be used in formulating long term policies regarding streamflow sensitivity in the study region. Doi: 10.28991/cej-2021-03091698 Full Text: PDF

AbstractThis study reports pollution source apportionment of surface waters and human health risk assessment based on 18 physicochemical and traces elements from 24 water quality monitoring sites for surface and groundwater around the two trans-boundary rivers of Pakistan: The Ravi and Sutlej. The principal component analysis identified 6 principal components (76.98 % cumulative variance) which are mainly caused by untreated industrial effluents, intense agricultural activities, and irrigation tailwater discharges. For all dissolved trace elements in surface waters, health hazard indices (HI) and hazard quotients (HQ) through ingestion and dermal contact are < 1 except As and Cr through ingestion only (for both adults and children). For adults and children, the HQingestion and HI values for As, Mn, Cu (for children only) and As, Fe, Mn (for children only) are > 1, indicating that As, Mn, Fe, and Cu are the most important pollutants causing chronic risks among the selected trace elements in both shallow and deep groundwater respectively. HQingestion, HQdermal, and HI values are higher for children than that of adults which shows the high susceptibility of children to these dissolved trace elements. The carcinogenic indices for the entire surface water elements exceed 10−6 through dermal and ingestion pathways suggesting carcinogenic health risk to the surrounding community. Hence, to protect human health, wastewater treatment plants and best management practices should be practiced to control point source and nonpoint source pollution respectively in the understudied area.

Understanding the influence of various variables on surface water quality is extremely important for protecting ecosystem health. The principal aim of this study is to assess the direct (DE), indirect (IE) and total effects (TE) of socio-economic, terrestrial and hydrological factors on surface water quality via path analysis through the lens of 15 sub-basins located on Indus basin, Pakistan. Four path models were selected based on Comparative Fit Index (CFI) = 0.999 value. First path model showed that rangelands having low population density decline river runoff which decreases instream Electrical Conductivity (EC) because of lower anthropogenic activities. Second path model depicted that croplands having higher population density enhance river runoff due to irrigation tail water discharge which decline instream EC because of dilution. Third path model showed that croplands with higher population density enhance river runoff which increases instream NO3 concentration because of unscientific application of irrigation water. Fourth path model unveiled that croplands enhance Gross Domestic Product (GDP) which enhance river runoff and instream NO3 concentration. To protect ecosystem health, Best Management Practices (BMPs), precision farming and modern irrigation techniques should be adopted to reduce irrigation tail water discharges containing pollutants entry in Indus River. Doi: 10.28991/cej-2021-03091683 Full Text: PDF

In this paper, a seismic hazard assessment (SHA) of the Shigo Kas hydropower project has been performed by deterministic and probabilistic approaches. The previously developed MATLAB-based code has been used for deterministic SHA, incorporating local site effects through deep soil analysis. On the other hand, for probabilistic SHA, CRISIS 2007 has been used through diffuse areal source zones. The latest updated earthquake instrumental and historical catalogs have been developed. Based on the recommendations of the International Commission on Large Dams, peak ground acceleration (PGA) values for the maximum credible earthquake (MCE), safety evaluation earthquake (SEE), design basis earthquake (DBE) and operating basis earthquake (OBE) have been assessed, which are 0.50 g, 0.68 g, 0.35 g and 0.24 g, respectively, at the intake location, and 0.50 g, 0.61 g, 0.30 g and 0.22 g, respectively, at the powerhouse location. Hazard maps have been developed for scenario-based earthquakes (MCE) and for the peak ground acceleration of 145-, 475- and 2500-year return periods. The de-aggregation process has evaluated the combined effects of magnitude and distance. At a distance of 30 to 70 km from the earthquake source, earthquakes of magnitude 5 Mw to 5.6 Mw and 5.9 Mw to 6.5 Mw are more hazardous for the current project.

No abstract