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India

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  • This dataset contains data on geomorphological characteristics and flow-related variables along the Beas River (Punjab, India) between Pong dam and Harike barrage in January 2020. The variables provided include cross-sectional area, water depth, river channel width, river flow velocity and dry-season discharge measured at ten reference sites with stable banks and straight, linear channels without islands or other mid-channel structures. Full details about this dataset can be found at https://doi.org/10.5285/f899fbc5-7034-45c0-a15c-9ee1d92a693f

  • This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'Historical' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection. Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used. BITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record.

  • This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation), using data derived from the ERA-Interim reanalysis data. Similar datasets were produced using various model output from the WCRP CMIP5 programme, available within the parent dataset collection. Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 450-300 hPa. This differs from those tracks from the CMIP5 data which were carried out on the 500 hPa layer. See linked documentation for details of the algorithms used. BITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record.

  • This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'RCP45' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection. Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used. BITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record.

  • Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This collection contains a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) produced from various model outputs. This work was undertaken as part of the NERC funded BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon and Poles) project. BITMAP was an Indo-UK-German project (NERC grant award: NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. Tracks of these WDs were generated using a bespoke tracking algorithm within the project applied to data from the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-Interim reanalysis data and model output from various experiments of the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (WCRP CMIP5). The algorithm, described in Hunt et al, 2017, QJRMS (see linked documentation), identified and linked upper-tropospheric vortices from the data and are available within this dataset collection. Additional details of the CMIP5 tracking algorithm are available in the Hunt et al. paper 'Representation of western disturbances in CMIP5 models' paper (see linked documentation). The principal difference between the algorithm used for the ERA-Interim data and the CMIP5 data is the choice of pressure levels on which the algorithm was run: 500 hPa for the ERA-Interim data and 450-300 hPa layer for the CMIP5 data.

  • This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'RCP85' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical' and 'RCP45' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection. Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used. BITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record.

  • Data are presented for daily rainfall, stream discharge and hydraulic conductivity of soils from catchments located in the Upper Nilgiris Reserve Forest in the state of Tamil Nadu. The catchments are dominated by four land cover types, shola, grassland, pine and wattle. The data were collected between May 2014 and December 2016. Tipping bucket wired rain gauges were used to measure rainfall. Stream discharge was measured from stilling wells and capacitance probe-based water level recorders. A mini-disk infiltrometer was used to measure the hydraulic conductivity of soils. Dry season data has not been included in this dataset as its focus is on extreme rain events. The data were collected as part of a series of eco-hydrology projects that explored the impact of land cover on rain-runoff response, carbon sequestration and nutrient and sediment discharge. The dataset presented here was collected by a team of three to five researchers and field assistants who were engaged in the installation of the data loggers and their regular operation and maintenance. Four research agencies have partnered across multiple projects to sustain the data collection efforts that started in June 2013 and continue (June 2020). These are the Foundation for Ecological Research, Advocacy and Learning - Pondicherry, the Ashoka Trust for Research in Ecology and the Environment - Bangalore, the Lancaster Environmental Centre, Lancaster University - UK, and the National Centre for Biological Sciences - Bangalore. Funding was provided by Ministry of Earth Sciences Government of India from the Changing Water Cycle programme (Grant Ref: MoES/NERC/16/02/10 PC-II) and the Hydrologic footprint of Invasive Alien Species project (MOES/PAMC/H&C/85/2016-PC-II). Additional funding was provided by UKRI Natural Environment Research Council grant NE/I022450/1 (Western Ghats-Capacity within the NERC Changing Water Cycle programme) and WWF-India as part of the Noyyal-Bhavani program.This research took place inside protected areas in the Nilgiri Division for which permissions and support were provided continually by the Tamil Nadu Forest Department, particularly the office of the District Forest Officer, Udhagamandalam. Full details about this dataset can be found at https://doi.org/10.5285/9257a999-2844-4be1-80d1-fd29e2ccf9ef

  • The data resource contains daily time-series of simulated streamflow, ground water levels and estimated demands, from humans, livestock, irrigation and industry, across the Cauvery Basin, India. The data were generated using the Global Water Availability Assessment (GWAVA) Model 5. A baseline of 1986-2005 is presented along with two future time slices (2041-2060 and 2061-2080) for these variables. The data were produced to help predict how rapid economic development and population growth in the region would impact on future water security. The data resource was produced by the data authors. The research was funded by NERC research grant NE/N016491/1 Upscaling Catchment Processes for Sustainable Water Management in Peninsular India Full details about this dataset can be found at https://doi.org/10.5285/522309f8-59b1-4982-85df-cb3171c2a062

  • This is a set of six ASCII grids describing the peak flood event for six return periods (2-100 years) at each point of the river network in the state of Kerala, India. Estimates were derived in a similar way to the Flood Estimation Handbook* approach. The data is measured in cubic metres per second, and is given on an unprojected resolution of 15 arc-seconds per grid cell. This work was supported by the Natural Environment Research Council as part of the LAWIS programme delivering National Capability. * (Flood Estimation Handbook. Centre for Ecology & Hydrology, 1999, ISBN: 9781906698003) Full details about this dataset can be found at https://doi.org/10.5285/cba9f9db-4706-4f1e-aaf4-fd7769e00db0

  • The database includes the classification of 966 active nitrogen-relevant policies from South Asia (including Afghanistan, Pakistan, India, Nepal, Bhutan, Bangladesh, the Maldives and Sri Lanka). The collection during 2020 and 2021 focuses on national level policies; some subnational policies were also collected. Data collection involved building on an existing open access global database developed by Kanter et al., 2020 that contained 51 policies for South Asia established to 2017 sourced by the environmental law ECOLEX database. Further policies were collected mostly from online sources: such as international policy databases: FAOLEX and national government and ministry websites. A protocol for policy collection and classification was established and followed to ensure consistent and thorough collections across the eight countries. Policies were classified according to a variety of parameters including the sink (air, water etc.) and sector (agriculture, industry etc.) they address and by type of policy. Policies were clustered if they had a central node policy in place and if a ‘subordinate policy’ (including amendments) did not offer anything new in terms of content related to Nitrogen management. This data was collected as part of a collective partnership that brings together leading organisations from across South Asia and the UK to reduce the adverse global impacts of nitrogen pollution on the environment, health, and wellbeing. More specifically providing a resource for both SANH partners and the wider scientific and policy community to understand the nitrogen policy landscape in the south Asian region. Furthermore, this research contributes to efforts in building a nitrogen policy arena promoting sustainable management of nitrogen, mitigating adverse effects. The dataset provides a thorough overview of available nitrogen related policies in South Asia but does not provide a complete set of all the nitrogen relevant policies available in each country. In some cases, this was due to our dependency on policy availability online, and some websites were not maintained. In addition, we excluded policies established post 2020 to avoid policy responses to COVID19 and to align more closely with the original global study. Repealed policies were omitted from the database. Full details about this dataset can be found at https://doi.org/10.5285/e2f248d5-79a1-4af9-bdd4-f739fb12ce9a