latowarr zylpah emylyna

0 views

Skip to first unread message

Queila Neubecker

unread,

Aug 3, 2024, 1:40:37 AM8/3/24

to cleancolacour

The Restoration Opportunities Atlas has been developed by WRI India with guidance from a technical working group comprising experts from leading organizations in the environment and development sectors. The atlas will help decision-makers develop broad pathways for achieving the NDC and to plan for landscape restoration at scale to achieve the Sustainable Development Goals.

The maps in the Map Collections materials were either published prior to \r1922, produced by the United States government, or both (see catalogue \rrecords that accompany each map for information regarding date of \rpublication and source). The Library of Congress is providing access to \rthese materials for educational and research purposes and is not aware of \rany U.S. copyright protection (see Title 17 of the United States Code) or any \rother restrictions in the Map Collection materials.\r

Note that the written permission of the copyright owners and/or other rights \rholders (such as publicity and/or privacy rights) is required for distribution, \rreproduction, or other use of protected items beyond that allowed by fair use \ror other statutory exemptions. Responsibility for making an independent \rlegal assessment of an item and securing any necessary permissions \rultimately rests with persons desiring to use the item.\r

The maps in the Map Collections materials were either published prior to 1922, produced by the United States government, or both (see catalogue records that accompany each map for information regarding date of publication and source). The Library of Congress is providing access to these materials for educational and research purposes and is not aware of any U.S. copyright protection (see Title 17 of the United States Code) or any other restrictions in the Map Collection materials.

Note that the written permission of the copyright owners and/or other rights holders (such as publicity and/or privacy rights) is required for distribution, reproduction, or other use of protected items beyond that allowed by fair use or other statutory exemptions. Responsibility for making an independent legal assessment of an item and securing any necessary permissions ultimately rests with persons desiring to use the item.

Jefferys, Thomas, -1771. The West-India atlas, or, A compendious description of the West-Indies: illustrated with forty correct charts and maps, taken from actual surveys: together with an historical account of the several countries and islands which compose that part of the world, their discovery, situation, extent, boundaries, product, trade, inhabitants, strength, government, religion, &c. London: Printed for Robert Sayer and John Bennett, 1775. Map.

Jefferys, T. (1775) The West-India atlas, or, A compendious description of the West-Indies: illustrated with forty correct charts and maps, taken from actual surveys: together with an historical account of the several countries and islands which compose that part of the world, their discovery, situation, extent, boundaries, product, trade, inhabitants, strength, government, religion, &c. London: Printed for Robert Sayer and John Bennett. [Map] Retrieved from the Library of Congress,

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Droughts are hydroclimatic extreme events that lead to prolonged periods of water scarcity, impacting agricultural production and food security worldwide1,2. Specifically, in monsoon-dominated regions like India, droughts have been recurrent3,4,5 and caused major famines in the 19th and 20th centuries6. The southwest monsoon rainfall in India is the primary source of agricultural water7 and groundwater recharge8,9, accounting for 80% of the total annual rainfall. Droughts in India due to the weakening of the southwest monsoon are closely linked to Indian Ocean warming and El Nino/Southern Oscillation (ENSO)7,10,11,12. Also, the diverse physiographic conditions and significant variability in rainfall patterns across India contribute to the varying intensities of drought events13.

India is highly vulnerable to drought with about two-thirds of its area prone to drought14,15,16. Being an agricultural-dominant country and home to 1.4 billion people, droughts in India profoundly impact agricultural productivity, water resource management, and socio-economic well-being. India has witnessed a rise in the frequency, severity, and duration of droughts over the recent decades, which is projected to be further exacerbated by climate change4,10,17,18,19. With the increasing food demand due to rising population and urbanization20,21, the impact of droughts is expected to become more severe in the future. Additionally, unsustainable pumping of groundwater adds further to the drought-induced challenges, increasing the risks in the future22,23.

We used satellite-based and reanalysis data products from CHIRPS and ERA5-Land to develop high-resolution precipitation and temperature. However, these hybrid datasets (CHIRPS and ERA5-Land) exhibit bias in space and time compared to observed datasets due to inadequate sampling, lack of ground-based observations, and error correction processes40,41. Consequently, the direct application of these datasets in studies related to climate change and hydroclimatic extremes may not be appropriate and straightforward. Several bias correction methods have been developed to address this challenge42,43,44,45,46,47. Bias correction involves a statistical transformation to modify the distribution of modelled data so that it closely resembles the observed data. We used the distribution (Quantile-Quantile) mapping bias correction method to reduce the bias in these datasets and making them consistent with the observed datasets. The distribution mapping method efficiently reduces bias for mean and interannual variations and also for extreme events48. Aadhar & Mishra27 compared linear scaling27,49,50 and distribution mapping43,50 for the bias correction of precipitation and temperature over South Asia and demonstrated that distribution mapping performs better than the linear scaling. Detailed information on distribution mapping methods is available in previous studies27,43,49.

SPEI was estimated at 1-month, 4-month, and 12-month time scales. The 1-month SPEI is essential for assessing the short-term meteorological drought and supports immediate decision-making. The 4-month SPEI monitors seasonal drought or wet conditions, providing insights into agricultural droughts. In contrast, the 12-month SPEI is more suitable for assessing the impact of droughts on surface and groundwater resources. We used 1-month SPEI to estimate monthly drought conditions for the summer monsoon months (JJAS) individually. We used 4-month SPEI at the end of September and January to estimate drought conditions for the summer monsoon and winter monsoon (ONDJ), respectively. Moreover, 12-month SPEI at the end of December and May were used to estimate drought conditions for the calendar year (Jan-Dec) and water year (Jun-May), respectively. Further, the gridded SPEI was used to evaluate the mean SPEI for India at country, states (including union territories), districts, and taluka (sub-district) levels. We computed mean SPEI for grids corresponding to each geographical level (country, states, districts, and talukas).

Finally, using the high-resolution (0.05) SPEI, we developed the Drought Atlas of India for each year between 1901 and 2020. The atlas includes the taluka-wise drought condition of summer monsoon, winter monsoon, calendar year, water year, and monsoon months (JJAS) for each year. As an example, we show drought condition for 1972 (Fig. 8), which was the second most exceptional monsoon season drought in India (Fig. 3A). The severity of the 1972 drought was exceptionally high for all the selected seasons (except winter monsoon) and for all monsoon months (Fig. 8).

We checked the accuracy of bias-corrected data against the reference data and noted significant improvements in its performance. However, despite the bias correction, potential bias may still exist65,66. The application of bias correction and interpolation techniques may also introduce random errors in the precipitation and temperature data42,67. Moreover, due to limited observations of climate variables, we estimated PET using the Hargreaves method, which may result in an overestimation of PET and drought4,68,69.

Development Data Lab presents the SHRUG Atlas. The portal is built on a collection of over 600,000 geographic units called "shrids". These geographic units allow us to aggregate satellite and census-derived data to consistent geographical areas and represent them via an interactive web-based portal. Each variable included in the portal is selectable from the layer menu, easily interrogated, and readily downloadable. For an interactive walkthrough of instructions on how to use the portal, please click the "Atlas Tour" button in the bottom left of the menu sidebar. Data is shown at both district and village/town level; zoom in (out) for more (less) detail.

The purpose of this platform is to democratize access to this information for researchers, policymakers, and the general public. To download the raw data, please visit the SHRUG download page, which also provides access to complete metadata tables describing all variables and datasets included on the platform. Please note that the complete data available for download includes more variables than are present on the visualization platform. We are continually working to improve this platform and the underlying data.