Rainwater Harvesting In A Typical Mine In Orissa

This paper discusses about the rainwater harvesting system and its implementation in a typical Mine area of Orissa, India as part of the solution to avoid water crisis in the future. It first reviewed the scenario of water availability, its distribution and shortages in the study region. In India and in the study region, we are blessed with an ample supply of water during Monsoon. However, rainwater is not available during non-monsoon period. Increasing water consumption by the industry, maintenance of dust due to crushing of rocks, plantations, vegetation and household users in the study region, had made existing water supply infrastructure strained. A study has been done to estimate the available runoff from the catchment area of a Mine in Orissa. ILWIS-GIS was used to delineate contours, drainage, land use and develop digital elevation model (DEM), flow accumulation, flow direction and aspect maps. Most suitable sites for water storage were obtained considering Best Management Practice (BMP) approach. Quantitative analysis was carried out using Rational method with runoff coefficient values to estimate the runoff volume available at different locations. The results indicate four sites suitable for water storages with some additional earthwork. Subsequently, for better accuracy and for and a robust approach, quantitative analysis was carried out using SCS-CN method with suitable CN value so obtained from the land use and other parameters to estimate the runoff volume available at different locations. The results indicate four sites suitable for water storages with some additional earthwork. Different scenarios were generated to obtain different runoff volumes and corresponding water spread area in the region. The length, breadth and depth required for each area is calculated using optimization approach to minimize the earthwork and maximize the plane surface

Simulating Marine Isotope Stage 7 with a coupled climate–ice sheet model

It is widely accepted that orbital variations are responsible for the generation of glacial cycles during the late Pleistocene. However, the relative contributions of the orbital forcing compared to CO2 variations and other feedback mechanisms causing the waxing and waning of ice sheets have not been fully understood. Testing theories of ice ages beyond statistical inferences, requires numerical modeling experiments that capture key features of glacial transitions. Here, we focus on the glacial buildup from Marine Isotope Stage (MIS) 7 to 6 covering the period from 240 to 170 ka (ka: thousand years before present). This transition from interglacial to glacial conditions includes one of the fastest Pleistocene glaciation–deglaciation events, which occurred during MIS 7e–7d–7c (236–218 ka). Using a newly developed three-dimensional coupled atmosphere–ocean–vegetation–ice sheet model (LOVECLIP), we simulate the transient evolution of Northern Hemisphere and Southern Hemisphere ice sheets during the MIS 7–6 period in response to orbital and greenhouse gas forcing. For a range of model parameters, the simulations capture the evolution of global ice volume well within the range of reconstructions. Over the MIS 7–6 period, it is demonstrated that glacial inceptions are more sensitive to orbital variations, whereas terminations from deep glacial conditions need both orbital and greenhouse gas forcings to work in unison. For some parameter values, the coupled model also exhibits a critical North American ice sheet configuration, beyond which a stationary-wave–ice-sheet topography feedback can trigger an unabated and unrealistic ice sheet growth. The strong parameter sensitivity found in this study originates from the fact that delicate mass imbalances, as well as errors, are integrated during a transient simulation for thousands of years. This poses a general challenge for transient coupled climate–ice sheet modeling, with such coupled paleo-simulations providing opportunities to constrain such parameters

CMIP5 Decadal Predictions: Implications for Australian Hydrology

Effective prediction of regional climate, especially rainfall, at interannual to decadal timescales is of considerable importance to decision makers. To investigate predictions at these timescales, a new set of climate model experiments, called the ‘decadal’ experiments was set up as part of CMIP5. Simulation of rainfall in climate models, however, is often poor and the decadal experiments provide little predictability for rainfall. Previous work has demonstrated that SST has greater predictability and sea surface temperature (SST) has a strong influence on terrestrial rainfall. Thus, SST predictions can be used to derive rainfall ahead of time. Such Indo-Pacific SST-rainfall relationships are used operationally in the seasonal forecasting of Australian rainfall. On this basis, the thesis investigates the possibility of rainfall prediction over Australia at interannual timescales using outputs of SST from these decadal experiments.The prediction skills of nine SST indices that are relevant predictors of Australian rainfall are first quantified. It is found that most indices are not predictable beyond the first year. Two approaches for enhancing their predictability timescale are examined: 1) Investigating the effect of drift on predictability and identifying the drift correction method that leads to the best predictability 2) Identifying other indices that inherently have a higher predictability.The key findings around model drift include: (i) under sampling of initialisation years can lead to spurious estimates of drift and predictability limits over the tropical Pacific, (ii) prediction skill is enhanced with more complicated drift correction methods, and (iii) drift correcting individual models prior to multi-model averaging leads to clear improvements in skill.This thesis also examined in detail a newly identified Pacific-Atlantic transbasin climate mode, TBV, to be significantly related to Australian rainfall. We found that this mode showed predictability timescales that exceeded El Niño Southern Oscillation (ENSO) across multiple models. Most importantly, we showed the co-occurrence of TBV and ENSO to intensify the drying and wetting effects of ENSO over Australia.Using all this information, a simple rainfall prediction model is designed and applied over Australia. The results show that there is indeed merit in decadal predictions of SST for interannual rainfall prediction over Australia

Evaluation of ERA5-Simulated Temperature and Its Extremes for Australia

Atmospheric reanalysis products offer high-resolution and long-term gridded datasets that can often be used as an alternative or a supplement to observational data. Although more accessible than typical observational data and deemed fit for climate change studies, reanalysis data can show biases resulting from data assimilation approaches. Thus, a thorough evaluation of the reanalysis product over the region and metric of study is critical. Here, we evaluate the performance of the latest generation of ECMWF reanalysis, ERA5, in simulating mean and extreme temperatures over Australia for 1979–2020 versus high-quality gridded observations. We find ERA5 generally simulates maximum and minimum temperatures reasonably well (mean bias ~1.5 °C), even though it underestimates/overestimates the daily maximum/minimum temperatures, leading to a cold bias for Tmax and a warm bias for Tmin. ERA5 also underestimates the decadal warming trend in both Tmax and Tmin compared to the observations. Furthermore, ERA5 struggles to simulate the temporal variability of Tmin, leading to a markedly worse skill in Tmin than Tmax. In terms of extreme indices, ERA5 is skilled at capturing the spatial and temporal patterns and trends of extremes, albeit with the presence of biases in each index. This can partially be attributed to the warm bias in the minimum temperature. Overall, ERA5 captures the mean and extreme temperature indices over the Australian continent reasonably well, warranting its potential to supplement observations in aiding climate change-related studies, downscaling for boundary conditions, and climate model evaluation

Simulating Marine Isotope Stage 7 with a coupled climate-ice sheet model

© Author(s) 2020. It is widely accepted that orbital variations are responsible for the generation of glacial cycles during the late Pleistocene. However, the relative contributions of the orbital forcing compared to CO2 variations and other feedback mechanisms causing the waxing and waning of ice-sheets have not been fully understood. Testing theories of ice-ages beyond statistical inferences, requires numerical modeling experiments that capture key features of glacial transitions. Here, we focus on the glacial build-up from Marine Isotope Stage (MIS) 7 to 6 covering the period from 240–170 ka (thousand years before present). This transition from interglacial to glacial conditions includes one of the fastest Pleistocene glaciation/deglaciation events which occurred during MIS 7e-7d-7c (236–218 ka). Using a newly developed three-dimensional coupled atmosphere-ocean-vegetation-ice-sheet model (LOVECLIP), we simulate the transient evolution of northern and southern hemisphere ice-sheets during the MIS 7-6 period in response to orbital and greenhouse-gas forcing. For a range of model parameters, the simulations capture the reconstructed evolution of global ice volume reasonably well. It is demonstrated that glacial inceptions are more sensitive to orbital variations, whereas terminations from deep glacial conditions need both orbital and greenhouse gas forcings to work in unison. For some parameter values, the coupled model also exhibits a critical North American ice sheet configuration, beyond which a stationary wave – ice-sheet topography feedback can trigger an unabated and unrealistic ice-sheet growth. The strong parameter sensitivity found in this study originates from the fact that delicate mass imbalances, as well as errors, are integrated during a transient simulation for thousands of years. This poses a general challenge for transient coupled climate-ice sheet modeling.11Nsciescopu

Future sea-level projections with a coupled atmosphere-ocean-ice-sheet model

Climate-forced, offline ice-sheet model simulations have been used extensively in assessing how much ice-sheets can contribute to future global sea-level rise. Typically, these model projections do not account for the two-way interactions between ice-sheets and climate. To quantify the impact of ice-ocean-atmosphere feedbacks, here we conduct greenhouse warming simulations with a coupled global climate-ice-sheet model of intermediate complexity. Following the Shared Socioeconomic Pathway (SSP) 1-1.9, 2-4.5, 5-8.5 emission scenarios, the model simulations ice-sheet contributions to global sea-level rise by 2150 of 0.2 ± 0.01, 0.5 ± 0.01 and 1.4 ± 0.1 m, respectively. Antarctic ocean-ice-sheet-ice-shelf interactions enhance future subsurface basal melting, while freshwater-induced atmospheric cooling reduces surface melting and iceberg calving. The combined effect is likely to decelerate global sea-level rise contributions from Antarctica relative to the uncoupled climate-forced ice-sheet model configuration. Our results demonstrate that estimates of future sea-level rise fundamentally depend on the complex interactions between ice-sheets, icebergs, ocean and the atmosphere. © 2023, The Author(s).11Ysciescopu

Design, evaluation and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble

NARCliM2.0 comprises two Weather Research and Forecasting (WRF) regional climate models (RCMs) downscaling five CMIP6 global climate models contributing to the Coordinated Regional Downscaling Experiment over Australasia at 20 km resolution, and south-east Australia at 4 km convection-permitting resolution. We first describe NARCliM2.0’s design, including selecting two, definitive RCMs via testing seventy-eight RCMs using different parameterisations for planetary boundary layer, microphysics, cumulus, radiation, and land surface model (LSM). We then assess NARCliM2.0's skill in simulating the historical climate versus CMIP3-forced NARCliM1.0 and CMIP5-forced NARCliM1.5 RCMs and compare differences in future climate projections. RCMs using the new Noah-MP LSM in WRF with default settings confer substantial improvements in simulating temperature variables versus RCMs using Noah-Unified. Noah-MP confers smaller improvements in simulating precipitation, except for large improvements over Australia’s southeast coast. Activating Noah-MP’s dynamic vegetation cover and/or runoff options primarily improve simulation of minimum temperature. NARCliM2.0 confers large reductions in maximum temperature bias versus NARCliM1.0 and 1.5 (1.x), with small absolute biases of ~0.5 K over many regions versus over ~2 K for NARCliM1.x. NARCliM2.0 reduces wet biases versus NARCliM1.x by as much as 50 %, but retains dry biases over Australia’s north. NARCliM2.0 is biased warmer for minimum temperature versus NARCliM1.5 which is partly inherited from stronger warm biases in CMIP6 versus CMIP5 GCMs. Under shared socioeconomic pathway (SSP)3-7.0, NARCliM2.0 projects ~3 K warming by 2060–79 over inland regions versus ~2.5 K over coastal regions. NARCliM2.0-SSP3-7.0 projects dry futures over most of Australia, except for wet futures over Australia’s north and parts of western Australia which are largest in summer. NARCliM2.0-SSP1-2.6 projects dry changes over Australia with only few exceptions. NARCliM2.0 is a valuable resource for assessing climate change impacts on societies and natural systems and informing resilience planning by reducing model biases versus earlier NARCliM generations and providing more up-to-date future climate projections utilising CMIP6