Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999

Deforestation is recognized as one of the most significant component in LULC and global changes scenario. It is imperative to assess its trend and the rates at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. In North-East India, one of the recognized global biodiversity hotspots, approximately 30% of total forest cover is under pressure of rapid land use changes. This region harbors variety of rare and endemic species of flora and fauna. It also has a strong bearing on regional climatic conditions. Extensive shifting cultivation, compounded by increasing population pressure and demands for agriculture land are the prime drivers in addition to other proximate drivers of deforestation. It is therefore of prime concern to analyse forest cover changes in the region, assess rate of change and extent and to identify the areas, which show repetitive changes. We analyzed forest cover maps from six temporal datasets based on satellite data interpretation, converted to geospatial database since 1972 till 1999. The states of Meghalaya, Nagaland and Tripura show highest changes in forest cover. Arunachal Pradesh shows least dynamic areas and maintains a good forest cover owing to its topographical inaccessibility in some areas. The present study reports the forest cover changes in the region using geospatial analysis and analyse them to devise proper management strategies.     

Impacts of COVID-19 on Sustainable Development Goals and effective approaches to maneuver them in the post-pandemic environment

Environmental Science and Pollution Research - In the pursuit of constructing a sustainable world for all through the instrumental seventeen Sustainable Development Goals, the COVID-19 pandemic...     

Wilk’s Method Based Model for Regulations Related to Radiological Impact of Opencast Uranium Mining on Water Reservoirs

Opencast mining of uranium may lead to natural erosion of ore material due to overland flow of water accumulated from rainfall. The overland flow may ultimately reach the nearby surface water body. This process may lead to the release of ²³⁸U and its daughter products into the surface water body. A model is developed to assess the radiological impact of the erosion in terms of dose through drinking water pathway due to ²³⁸U and its progeny in the surface water body. The in-growth of progeny is taken into account using Bateman equations. The study brings out the importance of incorporating decay chain transport in the radiological impact assessment studies. It is also observed that ²¹⁰Po, ²¹⁰Pb, ²²⁶Ra, and ²³⁰Th together contribute to about 95.5 % of the total dose. The model is then extended to incorporate the uncertainty associated with the dose due to consumption of the reservoir water by employing Wilk’s Method. Such a model can be very useful in establishing regulations related to dose through drinking water pathway around an opencast mine. Wilk’s method is computationally less expensive as compared to the exact methods like Monte Carlo method. Wilk’s method is used to calculate a value greater than α percentile value for the dose to the public due to ²³⁸U and its progeny in the reservoir through drinking water pathway with confidence level β (α/β value). When applied to a hypothetical case using some literature data on surface water bodies, it is found that with increase in the value of α or β, the α/β value in general, shows an increasing trend as expected. Depending upon the nature of the problem under study, one can calculate an α/β value i.e. 95/95 value, 99/95 value etc., and that value can be helpful in establishing the regulatory limiting value. Also, the α/β value can be used to check whether dose due to a particular radioactive release is within the specified limits.     

Inverse Modeling for Aquatic Source and Transport Parameters Identification and its Application to Fukushima Nuclear Accident

Inverse modeling technique based on nonlinear least square regression method (LSRM) is developed for the identification of aquatic source and transport parameters. Instantaneous line source release model in two-dimensional domain and continuous point source release model in three-dimensional domain are used for the purpose. Case studies have been carried out for both types of releases to illustrate their application. Error analysis has been carried out to identify the maximum error that can be tolerated in the input concentration data used in the inverse model and to specify the minimum number of sampling points to generate such input data. The LSRM is compared with the well-established correlation coefficient optimization method for instantaneous line source release model, and good comparison is observed between them. The LSRM is used to quantitatively estimate the releases of different radionuclides into the Pacific Ocean which has resulted due to the discharge of highly radioactive liquid effluent from the affected Daiichi Nuclear Power Station at Fukushima in Japan. The measured concentrations of these radionuclides in seawater samples collected from two sampling points near Fukushima are used for the estimation. The average release works out to be 1.09?×?10¹⁶ for ¹³¹I, 3.4?×?10¹⁵ Bq for ¹³⁴Cs, and 3.57?×?10¹⁵ Bq for ¹³⁷Cs. Very good agreement is observed between the releases estimated in this study and those estimated by other different agencies.     

Options for management of municipal solid waste in New York City: a preliminary comparison of health risks and policy implications

Landfill disposal and waste-to-energy (WTE) incineration remain the two principal options for managing municipal solid waste (MSW). One critical determinant of the acceptability of these options is the different health risks associated with each. In this analysis relying on published data and exposure modeling, we have performed health risk assessments for landfill disposal versus WTE treatment options for the management of New York City's MSW. These are based on the realistic scenario of using a waste transfer station (WTS) in Brooklyn and then transporting the untreated MSW by truck to a landfill in Pennsylvania or using a WTE facility in Brooklyn and then transporting the resultant ash by truck to a landfill in Pennsylvania. The overall results indicate that the individual cancer risks for both options would be considered generally acceptable, although the risk from landfilling is approximately 5 times greater than from WTE treatment; the individual non-cancer health risks for both options would be considered generally unacceptable, although once again the risk from landfilling is approximately 5 times greater than from WTE treatment. If one considers only the population in Brooklyn that would be directly affected by the siting of either a WTS or a WTE facility in their immediate neighborhood, individual cancer and non-cancer health risks for both options would be considered generally acceptable, but risks for the former remain considerably higher than for the latter. These results should be considered preliminary due to several limitations of this study such as: consideration of risks only from inhalation exposures; assumption that only volume and not composition of the waste stream is altered by WTE treatment; reliance on data from the literature rather than actual measurements of the sites considered, assuming comparability of the sites. However, the results of studies such as this, in conjunction with ecological, socioeconomic and equity considerations, should prove useful to environmental managers, regulators, policy makers, community representatives and other stakeholders in making sound and acceptable decisions regarding the optimal handling of MSW.     

Delivering Arsenic-free Drinking Water-Made Practically Possible: Continuous Scale Electrochemical Arsenic Remediation Process Furnished,based on Experimental Studies and ANN Simulation

Environment, Development and Sustainability - Arsenic (As) in groundwater has become a worldwide concern due to its high toxicity as it is classified as a potent carcinogen, when exposed to...     

Fate of coliforms and pathogenic parasite in four full-scale sewage treatment systems in India

Global positioning systems (GPS) are increasingly being used for habitat mapping because they provide spatially referenced data that can be used to characterize habitat structure across the landscape and document habitat change over time. We evaluated the accuracy of using a GPS for determining the size and location of habitat patches in a riverine environment. We simulated error attributable to a mapping-grade GPS receiver capable of achieving sub-meter accuracy onto discrete macrophyte bed and wood habitat patches (2 to 177 m(2)) that were digitized from an aerial photograph of the Laramie River, Wyoming, USA in a way that emulated field mapping. Patches with simulated error were compared to the original digitized patches. The accuracy in measuring habitat patches was affected most by patch size and less by patch shape and complexity. Perimeter length was consistently overestimated but was less biased for large, elongate patches with complex shapes. Patch area was slightly overestimated for small patches but was unbiased for large patches. Precision of area estimates was highest for large (>100 m(2)), elongate patches. Percent spatial overlap, a measure of the spatial accuracy of patch location, was low and variable for the smallest patches (2 to 5 m(2)). Mean percent spatial overlap was not related to patch shape but the precision of overlap was lower for small, elongate, and complex patches. Mapping habitat patches with a mapping-grade GPS can yield useful data, but research objectives will determine the acceptable amount of error and the smallest habitats that can be reliably measured.