Water Security最新文献

The present study investigates the interaction of the soil in Garhbaga village, located in the Rupnagar district of Punjab, India for As(V) adsorption under the influence of pH, contact time and varying arsenic concentrations. To understand the geochemical controls of arsenic mobilization in the region, batch sorption experiments were performed using soil obtained from arsenic contaminated district of Punjab. This study presents a novel approach by employing surface complexation models (SCMs) to investigate arsenic adsorption onto natural soils in the Punjab region, which has not been explored in previous literature. Furthermore, a comparison between Fe-based models, assuming ferrihydrite binding, and general composite (GC) approach, assuming adsorption on soil component surfaces, has not been conducted before, adding to the originality of this research. The adsorption kinetic experiment indicates about 70% adsorption of As(V) in about 4 h. The results of batch isotherm experiment shows that As(V) adsorption saturation onto the soil is reached at an aqueous concentration of about 0.89 mgL⁻¹. The results of the pH edges study shows a maximum As(V) adsorption of 93.88% at a pH of 4. The Langmuir’s isotherm was the best fitted because the value of linear regression coefficient (R² = 0.997) which verifies the monolayer adsorption of As(V). It was observed that the pseudo first order model best fitted for explaining the kinetic of As(V) adsorption onto the soil because it showed higher value of linear regression coefficient (R² = 0.995). Further, three different diffused layer models under varied assumptions were used to capture the batch experimental results. The surface complexation model with general-composite (GC) approach fairly predicted the experimental results when compared to Fe-oxide based models. The GC model was able to capture the observed experimental results for adsorption isotherm and pH edges for the soil within reasonable RMSE of 6.22 % and 7.97 %, respectively.

Anthropogenic water stress, especially in mountain habitats worldwide, affects water supply and threatens water security. Evaluating past trends, assessing current conditions, and anticipating future change is paramount for the sustainable use of increasingly scarce freshwater resources. This study simulates water yield using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to generate reliable information for decision-making related to watershed management programs in data-scarce Himalayan regions. The results are translated into watershed indices easily communicable to watershed managers, stakeholders and administrative agencies. The analysis demonstrates the utility of hydrological modeling using limited data within a scoping protocol for the pre-implementation phase of any watershed management program.

Conventional Flood Frequency Analysis (FFA) may underestimate flood quantiles and increase hydraulic infrastructure vulnerability in changing climates. This study uses annual maximum streamflow data from 17 hydrologic stations along west-flowing rivers in Kerala, India, for Non-Stationary (NS) FFA. The Generalized Extreme Value model with a linear temporal location parameter worked effectively for five stations. Kidangoor and Pattazhy stations must account for non-stationarity for longer return periods (RPs) (>50 years), whereas Neeleeswaram and Perumannu stations must for shorter RPs (<50 years). An extensive study was conducted for Neeleswaram station (Periyar basin) by simulating NS models incorporating four large-scale climate oscillations as covariates. The stationary assumption underestimated flood return levels of 2-year RP by about 61% which increases the flood risk leading to failure of hydraulic infrastructures. It was observed that the best fitted climate-based NS model achieves stationary return level of 150-years RP at 25-years RP itself. The study proved that the climate-based NS models captured the 2018 August Floods in Periyar basin better than stationary and time-based models. The regional variability in FF curve behaviour concludes that NSFFA for Kerala cannot be generalised and must be done at a local-scale.

Due to a changing climate and increased urbanization, an escalation of urban flooding occurrences and its aftereffects are ever more dire. Notably, the frequency of extreme storms is expected to increase, and as built environments impede the absorption of water, the threat of loss of human life and property damages exceeding billions of dollars are heightened. Hence, agencies and organizations are implementing novel modeling methods to combat the consequences. This review details the concepts, impacts, and causes of urban flooding, along with the associated modeling endeavors. Moreover, this review describes contemporary directions towards urban flood resolutions, including the more recent hydraulic-hydrologic models that use modern computing architecture and the trending applications of artificial intelligence/machine learning techniques and crowdsourced data. Ultimately, a reference of utility is provided, as scientists and engineers are given an outline of the recent advances in urban flooding research.

Bangladesh is increasingly experiencing different challenges from scarce drinking water sources and health risks, explicitly or implicitly attributed to climate change. This systematic bibliographic review manually screened 47 articles under four categories, including Water and health; Climate and water; Climate and health; and Climate, water, and health, from 2010 to 2022. This research is critical for ensuring the availability of safe drinkable water and public health adaptation to climate change in Bangladesh. The findings revealed that cholera, infant diarrhea, pneumonia, dengue, and malaria are prevalent in the vulnerable groups. The present number and distribution of regional healthcare centers demonstrates potable water procedures and medical centers are insufficient relative to demands. Overall, this study revealed several techniques that help guarantee safe potable water, including holding rainwater, pond sand filters, and drinkable water supply. A knowledge-based approach was used to propound an adaptation framework for tackling the impact of changing climate, especially on safe water availability and public health, and also identified six research gaps. This research serves as a roadmap for future scholars, academicians, practitioners, and policymakers and indicates the need for more progress in the database on national climate change research.

A review of ecological, social, engineering, and integrative approaches to define and apply resilience thinking is presented and comparatively discussed in the context of watershed management. Knowledge gaps are identified through an assessment of this literature and compilation of a set of research questions through stakeholder engagement activities. We derive a proposed research agenda describing key areas of inquiry such as watershed resilience variables and their interactions; leveraging watershed natural properties, processes, and dynamics to facilitate and enable resilience; analytical methods and tools including monitoring, modeling, metrics, and scenario planning, and their applications to watersheds at different spatial and temporal scales, and infusing resilience concepts as core values in watershed adaptive management.