scholarly journals An evaluation of vegetation health and the socioeconomic dimension of the vulnerability of Jharkhand state of India in climate change scenarios and their likely impact: a geospatial approach

2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Firoz Ahmad ◽  
Md Meraj Uddin ◽  
Laxmi Goparaju
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Forest Fire ◽  
Future Climate ◽  
Future Climate Change ◽  
Land Use Land Cover ◽  
Tribal Population ◽  
Agricultural Vulnerability

AbstractGeospatial evaluation of various datasets is extremely important because it gives a better comprehension of the past, present and future and can therefore be significantly utilized in effective decision making strategies. This study examined the relationships, using geospatial tools, between various diversified datasets such as land use/land cover (LULC), long term Normalized Difference Vegetation Index (NDVI) based changes, long term forest fire points, poverty percentage, tribal percentage, forest fire hotspots, climate change vulnerability, agricultural vulnerability and future (2030) climate change anomalies (RCP-6) of Jharkhand state, India, for a better understanding and knowledge of its vegetation health, LULC, poverty, tribal population and future climate change impact. The long term NDVI (1982-2006) evaluation revealed negative change trends in seven northwest districts of Jharkhand state, these were: Hazaribag, Ramgarh, Palamu, Lohardaga, Chatra, Garhwa and Latehar. The forests as well as the agriculture of these districts have lost their greenness during this period. The forest fire frequency events were found to be more pronounced in the land use/land cover of “tropical lowland forests, broadleaved, evergreen, <1000 m” category, and were roughly twice the intensity of the “tropical mixed deciduous and dry deciduous forests” category. In the nine districts of Jharkhand it was found that 40 % of the population was living below the poverty line which is around twice the national average. The highest poverty districts, in percentage, were: Garwah (53.93), Palamu (49.24), Latehar (47.99) and Chatra (46.2). The southwest and south of Jharkhand state shows a tribal population density of more than 40%. The climate change vulnerability was found to be highest in the district of Saraikela followed by Pashchim Singhbhum, whereas agricultural vulnerability was found to be highest in the district of Pashchim Singhbhum followed by Saraikela, Garhwa, Simdega, Latehar, Palamu and Lohardaga. The temperature anomalies prediction for the year 2030 shows an increasing trend in temperature with values of 0.8°C to 1°C in the state of Jharkhand. The highest increases were observed in the districts of Pashchim Singhbhum, Simdega and Saraikela. Based on these evaluations we can conclude that a few of the districts of Jharkhand, such as Pashchim Singhbhum, Garhwa, Palamu and Latehar need to be prioritized for development on an urgent basis. The outcomes of this study would certainly guide the policymakers to prepare more robust plans when keeping in mind the future climate change impacts for the prioritization of various districts of Jharkhand which suffer from extreme poverty, diminished livelihood and insignificant agricultural productivity for the betterment of the people of Jharkhand based on their adaptive capacity.

Combined impact of Climate change and Land use on water quality in the mid-21st century: A modelling study for a highly industrialized stretch of Ganga River

2021 ◽  
Author(s):  
Sneha Santy ◽  
Pradeep Mujumdar ◽  
Govindasamy Bala
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
General Circulation ◽  
General Circulation Models ◽  
Ganga River ◽  
Quality Analysis ◽  
Future Climate Change ◽  
Land Use Land Cover

&lt;p&gt;High industrial discharge, excessive agricultural activities, untreated sewage disposal make the Kanpur region one of the most contaminated stretches of the Ganga river. This study analyses water quality for the combined future climate change and land use land cover scenarios for mid-century for a 238km long Kanpur stretch of Ganga river. Climate change projections from 21 General Circulation Models for the scenarios of RCP 4.5 and RCP 8.5 are considered and Land use Land Cover (LULC) projections are made with QGIS software. Streamflow and water temperature are modelled using the HEC-HMS model and a Water-Air temperature regression model, respectively. Water quality analysis is simulated using the QUAL2K model in terms of nine water quality parameters, dissolved oxygen, biochemical oxygen demand (BOD), ammonia nitrogen, nitrate nitrogen, total nitrogen, organic phosphorus, inorganic phosphorus, total phosphorus and faecal coliform. Climate change impact alone is projected to result in degraded water quality in the future. Combined climate change and LULC change may further degrade water quality, especially at the study area's critical locations. Our study will provide guidance to policymakers to safeguard the Ganga river from further pollution.&lt;/p&gt;

scholarly journals Long-Term Land Use Land Cover Change in Urban Centers of Southwest Ethiopia From a Climate Change Perspective

2020 ◽  
Vol 2 ◽  
Author(s):  
Tesfaye Dessu ◽  
Diriba Korecha ◽  
Debela Hunde ◽  
Adefires Worku
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Kendall Test ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Southwest Ethiopia ◽  
Mann Kendall Test

Long-term urban land use land cover change (LULCC) dynamics and climate change trends in Southwest Ethiopia's four urban centers were examined for 60 years. Remote sensing, aerial photos, and Landsat, temperature, and rainfall data were analyzed from a climate change perspective over the Jimma, Bedelle, Bonga, and Sokorru urban centers of southwest Ethiopia from 1953 to 2018. Based on geospatial analysis and maximum likelihood supervised image classification techniques to classify LULCC categories, the Mann-Kendall test was applied to perform trend analyses on temperature and rainfall. The LULCC analysis revealed that built-up areas over the urban centers had shown an increasing trend, with the highest increment by 2,360 hectares over Jimma, while vegetation, wetland, and cropland declined due to conversion of plain lands to built-up areas and other similar zones. The pronounced decline of vegetation coverage was 1,427, 185,116, and 32 hectares in Jimma, Bedelle, Bonga, and Sokorru, respectively. Mann-Kendall test results showed a significant sign of intra-seasonal and inter-annual variability of rainfall while the summer and annual rainfall patterns remained less variable compared to other seasons. This study's findings revealed that when the mean between the two climatic normals of 1953–86 is compared with 1987–2018, the temperature has significantly increased in the latter three decades. The rapid expansion of built-up areas coupled with a sharp decline of green space or vegetation and agricultural/croplands could lead to gradual changes in LULCC classes, which have contributed to the changing of the local climate, especially the surface temperature and rainfall over the urban centers of southwest Ethiopia. Therefore, we recommend that the local urban administrations emphasize sustainable urban development by integrating urban planning policies with land use to protect the environment by adopting local municipal adaptation and national climate change strategies. Restoration of the local environment and creation of climate-smart cities could be critical to the resilience of urban dwellers and ecosystems to the changing climate by enhancing grass-root climate services. To that end, we recommend further advanced research to understand how urban LULC-related changes and other factors contribute to local and regional climates, as urban areas of Southwest Ethiopia are undergoing a rapid transformation of their rural surroundings.

scholarly journals Evaluation of long term forest fires in India with respect to state administrative boundary, forest category of LULC and future climate change scenario: A Geospatial Perspective

2018 ◽  
Vol 79 (4) ◽  
pp. 335-343
Author(s):  
Firoz Ahmad ◽  
Md Meraj Uddin ◽  
Laxmi Goparaju
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Forest Fires ◽  
Climate Change Scenario ◽  
Fire Frequency ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Future Climate Change Scenario

Abstract Analysing the forest fires events in climate change scenario is essential for protecting the forest from further degradation. Geospatial technology is one of the advanced tools that has enormous capacity to evaluate the number of data sets simultaneously and to analyse the hidden relationships and trends. This study has evaluated the long term forest fire events with respect to India’s state boundary, its seasonal monthly trend, all forest categories of LULC and future climate anomalies datasets over the Indian region. Furthermore, the spatial analysis revealed the trend and their relationship. The state wise evaluation of forest fire events reflects that the state of Mizoram has the highest forest fire frequency percentage (11.33%) followed by Chhattisgarh (9.39%), Orissa (9.18%), Madhya Pradesh (8.56%), Assam (8.45%), Maharashtra (7.35%), Manipur (6.94%), Andhra Pradesh (5.49%), Meghalaya (4.86%) and Telangana (4.23%) when compared to the total country’s forest fire counts. The various LULC categories which represent the forest show some notable forest fire trends. The category ‘Deciduous Broadleaf Forest’ retain the highest fire frequency equivalent to 38.1% followed by ‘Mixed Forest’ (25.6%), ‘Evergreen Broadleaf Forest’ (16.5%), ‘Deciduous Needle leaf Forest’ (11.5%), ‘Shrub land’ (5.5%), ‘Evergreen Needle leaf Forest’ (1.5%) and ‘Plantations’ (1.2%). Monthly seasonal variation of forest fire events reveal the highest forest fire frequency percentage in the month of ‘March’ (55.4%) followed by ‘April’ (28.2%), ‘February’ (8.1%), ‘May’ (6.7%), ‘June’ (0.9%) and ‘January’ (0.7%). The evaluation of future climate data for the year 2030 shows significant increase in forest fire seasonal temperature and abrupt annual rainfall pattern; therefore, future forest fires will be more intensified in large parts of India, whereas it will be more crucial for some of the states such as Orissa, Chhattisgarh, Mizoram, Assam and in the lower Sivalik range of Himalaya. The deciduous forests will further degrade in future. The highlight/results of this study have very high importance because such spatial relationship among the various datasets is analysed at the country level in view of the future climate scenario. Such analysis gives insight to the policymakers to make sustainable future plans for prioritization of the various state forests suffering from forest fire keeping in mind the future climate change scenario.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Climate ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 83
Author(s):  
Geofrey Gabiri ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Constanze Leemhuis ◽  
Roderick van der Linden ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Rainy Season ◽  
Hydrological Processes ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Inland Valley ◽  
Headwater Catchment

The impact of climate and land use/land cover (LULC) change continues to threaten water resources availability for the agriculturally used inland valley wetlands and their catchments in East Africa. This study assessed climate and LULC change impacts on the hydrological processes of a tropical headwater inland valley catchment in Uganda. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze climate and LULC change impacts on the hydrological processes. An ensemble of six regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment for two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were used for climate change assessment for historical (1976–2005) and future climate (2021–2050). Four LULC scenarios defined as exploitation, total conservation, slope conservation, and protection of headwater catchment were considered. The results indicate an increase in precipitation by 7.4% and 21.8% of the annual averages in the future under RCP4.5 and RCP8.5, respectively. Future wet conditions are more pronounced in the short rainy season than in the long rainy season. Flooding intensity is likely to increase during the rainy season with low flows more pronounced in the dry season. Increases in future annual averages of water yield (29.0% and 42.7% under RCP4.5 and RCP8.5, respectively) and surface runoff (37.6% and 51.8% under RCP4.5 and RCP8.5, respectively) relative to the historical simulations are projected. LULC and climate change individually will cause changes in the inland valley hydrological processes, but more pronounced changes are expected if the drivers are combined, although LULC changes will have a dominant influence. Adoption of total conservation, slope conservation and protection of headwater catchment LULC scenarios will significantly reduce climate change impacts on water resources in the inland valley. Thus, if sustainable climate-smart management practices are adopted, the availability of water resources for human consumption and agricultural production will increase.

scholarly journals Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

2013 ◽  
Vol 8 (1) ◽  
pp. 084596 ◽  
Author(s):  
Zhongchang Sun ◽  
Xinwu Li ◽  
Wenxue Fu ◽  
Yingkui Li ◽  
Dongsheng Tang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Surface Runoff ◽  
Urban Areas ◽  
Land Use Land Cover ◽  
Long Term Effects ◽  
Effects Of Land Use ◽  
Beijing China

Are there pre-Quaternary geological analogues for a future greenhouse warming?

2011 ◽  
Vol 369 (1938) ◽  
pp. 933-956 ◽  
Author(s):  
Alan M. Haywood ◽  
Andy Ridgwell ◽  
Daniel J. Lunt ◽  
Daniel J. Hill ◽  
Matthew J. Pound ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Future Climate ◽  
Future Climate Change ◽  
Anthropogenic Emissions ◽  
Earth System ◽  
System Sensitivity ◽  
Earth History ◽  
Scientific Papers

Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race’s current grand climate experiment . This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean–atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene–Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO 2 forcing—whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate—or the sensitivity of the climate system itself to CO 2 was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO 2 ) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO 2 concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO 2 thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.

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