ExtendinG SUb-DAily River Discharge data over INdia (GUARDIAN).

River discharge information is crucial for various applications, but the measurement process often remains impeded by factors that hinder near real-time (NRT) data availability in India. However, leveraging telemetry-based water surface elevation (WSE) data across the country provides an opportunity to convert it into river discharge. This conversion is made possible by utilizing rating curves (RCs) derived from historical collocated measurements of WSE and discharge.

Thermal illusions for thermal displays: a review.

Thermal illusions, a subset of haptic illusions, have historically faced technical challenges and limited exploration. They have been underutilized in prior studies related to thermal displays. This review paper primarily aims to comprehensively categorize thermal illusions, offering insights for diverse applications in thermal display design.

Warming inhibits increases in vegetation net primary productivity despite greening in India.

India is the second-highest contributor to the post-2000 global greening. However, with satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001-2019 fails to translate into increased carbon uptake due to warming constraints.

Framework for global sensitivity analysis in a complex 1D-2D coupled hydrodynamic model: Highlighting its importance on flood management over large data-scarce regions.

Sensitivity analysis determines how perturbation or variation in the values of an independent variable affects a particular dependent variable. The present study attempts to comprehend the sensitivity of the static input parameters on the accuracy of the outputs in a hydrodynamic flood model, which subsequently improves the model accuracy. Hydrodynamic flood modeling is computationally strenuous and data-intensive.

Rainwater harvesting and water balance simulation-optimization scheme to plan sustainable second crop in small rain-fed systems.

Environmental degradation in the form of water shortage and uncertainty has severely affected the food systems across the globe. Especially in India, which is dominated by rain-fed farmers, the need for sustainable water resource and its management at farm level is imperative for farming livelihoods and food security of the country. Rainwater harvesting in on-farm reservoirs (OFR) can enable crop diversification, year round cropping and seasonal vegetable cultivation in rain-fed farming systems in India.

A novel flood risk mapping approach with machine learning considering geomorphic and socio-economic vulnerability dimensions.

Quantifying flood hazards by employing hydraulic/hydrodynamic models for flood risk mapping is a widely implemented non-structural flood management strategy. However, the unavailability of multi-domain and multi-dimensional input data and expensive computational resources limit its application in resource-constrained regions. The fifth and sixth IPCC assessment reports recommend including vulnerability and exposure components along with hazards for capturing risk on human-environment systems from natural and anthropogenic sources.

Risk mapping of Indian coastal districts using IPCC-AR5 framework and multi-attribute decision-making approach.

Strategic location of coastal areas across the world causes them to be prone to disaster risks. In the global south, the Indian coast is one of the most susceptible to oceanic extreme events, such as cyclones, storm surge and high tides. This study provides an understanding of the risk experienced (currently as well as back in 2001) by the districts along the Indian coastline by developing a quantitative risk index.

An integrated approach for modeling uncertainty in human health risk assessment.

A human health risk assessment (HHRA) will not remain simple and straightforward when it involves multiple uncertain input variables. Uncertainties in HHRA result from the unavailability and subjectivity of input variables. Though several studies have performed HHRA, the quantification of uncertainty in HHRA under a situation of data scarcity and the simultaneous application of random and non-random input variables have rarely been reported.

WebFRIS: An efficient web-based decision support tool to disseminate end-to-end risk information for flood management.

The present study describes the development of a web-based flood risk information system 'WebFRIS' for Jagatsinghpur district, a severely flood-prone region in Eastern India. The WebFRIS is designed by using various readily available open-source web tools and packages such as Google Map, PHP, MySQL, and JSON. Special emphasis is directed towards designing the layout and architecture, to be easily accessible by any end-user irrespective of any technical know-how.

Rationalization of water quality monitoring locations under spatiotemporal heterogeneity of diffuse pollution using seasonal export coefficient.

Water quality is continuously changing because of anthropogenic origin of point and diffuses (non-point) pollution sources. Most of the time diffuse sources are not considered for rationalization of sampling sites as their accurate estimation is tedious and data intensive. The estimation of diffuse pollution is conventionally carried out using observed water quality data.

A two-stage multi-attribute decision-making model for selecting appropriate locations of waste transfer stations in urban centers.

Selecting appropriate locations for municipal solid waste (MSW) management facilities, such as transfer stations, is an important issue in rapidly developing regions. Multiple alternatives and evaluation attributes need to be analyzed for finalizing the locations of these facilities. Multi-attribute decision-making (MADM) approaches are found to be very effective for ranking several potential locations and hence selecting the best among them based on the identified attributes.

Large-scale dynamics have greater role than thermodynamics in driving precipitation extremes over India.

The changing characteristics of precipitation extremes under global warming have recently received tremendous attention, yet the mechanisms are still insufficiently understood. The present study attempts to understand these processes over India by separating the 'dynamic' and 'thermodynamic' components of precipitation extremes using a suite of observed and reanalysis datasets. The former is mainly due to changes in atmospheric motion, while the latter is driven mainly by the changes associated with atmospheric moisture content.

A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions.

Identification of flood-risk dynamics is pivotal for refurbishing the existing and future flood-management options. The present study quantifies the marginal and compound contributions of hazard and vulnerability to flood-risk through an innovative concept of Risk-classifier, designed in the form of a 5 × 5 choropleth. The proposed framework is demonstrated at the finest administrative scale of village-level over Jagatsinghpur district in Mahanadi River basin, Odisha (India) for two-time frames: Scenario-I (1970-2011) and Scenario-II (1970-2001).

Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization.

While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014-2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM).

A long-term comparative assessment of human health risk to leachate-contaminated groundwater from heavy metal with different liner systems.

The handling and management of municipal solid waste (MSW) are major challenges for solid waste management in developing countries. Open dumping is still the most common waste disposal method in India. However, landfilling also causes various environmental, social, and human health impacts.

A facility location model for municipal solid waste management system under uncertain environment.

In municipal solid waste management system, decision makers have to develop an insight into the processes namely, waste generation, collection, transportation, processing, and disposal methods. Many parameters (e.g.

A Framework for Assessing Uncertainty Associated with Human Health Risks from MSW Landfill Leachate Contamination.

Landfilling is a cost-effective method, which makes it a widely used practice around the world, especially in developing countries. However, because of the improper management of landfills, high leachate leakage can have adverse impacts on soils, plants, groundwater, aquatic organisms, and, subsequently, human health. A comprehensive survey of the literature finds that the probabilistic quantification of uncertainty based on estimations of the human health risks due to landfill leachate contamination has rarely been reported.

Lack of Dependence of Indian Summer Monsoon Rainfall Extremes on Temperature: An Observational Evidence.

The intensification of precipitation extremes in a warming world has been reported on a global scale and is traditionally explained with the Clausius-Clapeyron (C-C) relation. The relationship is observed to be valid in mid-latitudes; however, the debate persists in tropical monsoon regions, with the extremes of the Indian Summer Monsoon Rainfall (ISMR) being a prime example. Here, we present a comprehensive study on the dependence of ISMR extremes on both the 2 m surface air temperature over India and on the sea surface temperature over the tropical Indian Ocean.

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked.

A framework for assessment and characterisation of municipal solid waste landfill leachate: an application to the Turbhe landfill, Navi Mumbai, India.

Rapid industrialisation, growing population and changing lifestyles are the root causes for the generation of huge amounts of solid waste in developing countries. In India, disposal of municipal solid waste (MSW) through open dumping is the most common waste disposal method. Unfortunately, leachate generation from landfill is high due to the prolonged and prominent monsoon season in India.

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

The design of surface water quality sampling location is a crucial decision-making process for rationalization of monitoring network. The quantity, quality, and types of available dataset (watershed characteristics and water quality data) may affect the selection of appropriate design methodology. The modified Sanders approach and multivariate statistical techniques [particularly factor analysis (FA)/principal component analysis (PCA)] are well-accepted and widely used techniques for design of sampling locations.

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads.

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks.

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India).

Unlabelled: The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented.

The influence of expert opinions on the selection of wastewater treatment alternatives: a group decision-making approach.

The application of multiple-attribute decision-making (MADM) to real life decision problems suggests that avoiding the loss of information through scenario-based approaches and including expert opinions in the decision-making process are two major challenges that require more research efforts. Recently, a wastewater treatment technology selection effort has been made with a 'scenario-based' method of MADM. This paper focuses on a novel approach to incorporate expert opinions into the scenario-based decision-making process, as expert opinions play a major role in the selection of treatment technologies.

Selection of an appropriate wastewater treatment technology: a scenario-based multiple-attribute decision-making approach.

Many technological alternatives for wastewater treatment are available, ranging from advanced technologies to conventional treatment options. It is difficult to select the most appropriate technology from among a set of available alternatives to treat wastewater at a particular location. Many factors, such as capital costs, operation and maintenance costs and land requirement, are involved in the decision-making process.