scholarly journals Modelling impact of future climate and land use land cover on flood vulnerability for policy support – Hyderabad, India

Water Policy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 733-747
Author(s):  
Swathi Vemula ◽  
K. Srinivasa Raju ◽  
S. Sai Veena

Abstract The study analyses the impact of climate change and land use land cover (LULC) on runoff of Hyderabad city, India for the years 1995, 2005, 2016 and 2031. Flood vulnerability was evaluated for extreme historic and future rainfall events. Maximum daily rainfalls of 132, 181 and 165 mm that occurred in the decades of 1990–2000, 2001–2010 and 2011–2016 were considered for historic rainfall–runoff modelling. Complementarily in climate change, maximum daily rainfall of 266 mm predicted during 2020–2040 by Geophysical Fluid Dynamics Laboratory-Coupled Model 3 (GFDL-CM3) Representative Concentration Pathway (RCP) 2.6, was analysed for rainfall-runoff scenario in 2031. LULC was assessed from historic maps and the master plan of the city. Peak runoff was modelled in Storm Water Management Model (SWMM) for corresponding daily rainfall and LULC. The floodplain of the river Musi was modelled in Hydrological Engineering Center-River Analysis System (HEC-RAS). Results showed that changing rainfall and LULC increased peak runoff by three times, and flood depth in the river increased by 22% from 1995 to 2031. In 2016 and 2031, 48 and 51% of the city was highly vulnerable. Five detention basins were proposed to combat increasing runoff, due to which highly vulnerable areas reduced by 8% in 2016 and 9% in 2031.

Hydrology ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 2 ◽  
Author(s):  
Kinati Chimdessa ◽  
Shoeb Quraishi ◽  
Asfaw Kebede ◽  
Tena Alamirew

In the Didessa river basin, which is found in Ethiopia, the human population number is increasing at an alarming rate. The conversion of forests, shrub and grasslands into cropland has increased in parallel with the population increase. The land use/land cover change (LULCC) that has been undertaken in the river basin combined with climate change may have affected the Didessa river flow and soil loss. Therefore, this study was designed to assess the impact of LULCC on the Didessa river flow and soil loss under historical and future climates. Land use/land cover (LULC) of the years 1986, 2001 and 2015 were independently combined with the historical climate to assess their individual impacts on river flow and soil loss. Further, the impact of future climates under Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) scenarios on river flow and soil loss was assessed by combining the pathways with the 2015 LULC. A physically based Soil and Water Assessment Tool (SWAT2012) model in the ArcGIS 10.4.1 interface was used to realize the purpose. Results of the study revealed that LULCC that occurred between 1986 and 2015 resulted in increased average sediment yield by 20.9 t ha−1 yr−1. Climate change under RCP2.6, RCP4.5 and RCP8.5 combined with 2015 LULC increased annual average soil losses by 31.3, 50.9 and 83.5 t ha−1 yr−1 compared with the 2015 LULC under historical climate data. It was also found that 13.4%, 47.1% and 87.0% of the total area may experience high soil loss under RCP2.6, RCP4.5 and RCP8.5, respectively. Annual soil losses of five top-priority sub catchments range from 62.8 to 57.7 per hectare. Nash Stuncliffe Simulation efficiency (NSE) and R2 values during model calibration and validation indicated good agreement between observed and simulated values both for flow and sediment yield.


2019 ◽  
Vol 11 (24) ◽  
pp. 7083 ◽  
Author(s):  
Kristian Näschen ◽  
Bernd Diekkrüger ◽  
Mariele Evers ◽  
Britta Höllermann ◽  
Stefanie Steinbach ◽  
...  

Many parts of sub-Saharan Africa (SSA) are prone to land use and land cover change (LULCC). In many cases, natural systems are converted into agricultural land to feed the growing population. However, despite climate change being a major focus nowadays, the impacts of these conversions on water resources, which are essential for agricultural production, is still often neglected, jeopardizing the sustainability of the socio-ecological system. This study investigates historic land use/land cover (LULC) patterns as well as potential future LULCC and its effect on water quantities in a complex tropical catchment in Tanzania. It then compares the results using two climate change scenarios. The Land Change Modeler (LCM) is used to analyze and to project LULC patterns until 2030 and the Soil and Water Assessment Tool (SWAT) is utilized to simulate the water balance under various LULC conditions. Results show decreasing low flows by 6–8% for the LULC scenarios, whereas high flows increase by up to 84% for the combined LULC and climate change scenarios. The effect of climate change is stronger compared to the effect of LULCC, but also contains higher uncertainties. The effects of LULCC are more distinct, although crop specific effects show diverging effects on water balance components. This study develops a methodology for quantifying the impact of land use and climate change and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes (low flow and floods) and determines hot spots, which are critical for environmental development.


Author(s):  
R. M. Devi ◽  
B. Sinha ◽  
J. Bisaria ◽  
S. Saran

<p><strong>Abstract.</strong> Forest ecosystems play a key role in global ecological balance and provide a variety of tangible and intangible ecosystem services that support the livelihoods of rural poor. In addition to the anthropogenic pressure on the forest resources, climate change is also impacting vegetation productivity, biomass and phenological patterns of the forest. There are many studies reported all over the world which use change in Land Use Land Cover (LULC) to assess the impact of climate change on the forest. Land use change (LC) refers to any anthropogenic or natural changes in the terrestrial ecosystem at a variety of spatial or temporal scale. Changes in LULC induced by any causes (natural/anthropogenic) play a major role in global as well as regional scale pattern which in turn affects weather and climate. Remote sensing (RS) data along with Geographic Information System (GIS) help in inventorying, mapping and monitoring of earth resources for effective and sustainable landscape management of forest areas. Accurate information about the current and past LULC including natural forest cover along with accurate means of monitoring the changes are very necessary to design future adaptation strategies and formulation of policies in tune of climate change. Therefore, this study attempts to analyze the changes of LULC of Kanha Tiger Reserve (KTR) due to climate change. The rationale for selecting KTR is to have a largely intact forest area without any interference so that any change in LULC could be attributed to the impact of climate change. The change analysis depicted changes in land use land cover (LULC) pattern by using multi-temporal satellite data over a period of time. Further, these detected changes in different LULC class influence the livelihoods of forest-dependent communities. As the study site is a Sal dominated landscape; the findings could be applied in other Sal dominated landscape of central India in making future policies, adaptation strategies and silvicultural practices for reducing the vulnerability of forest-dependent communities.</p>


2019 ◽  
Vol 8 (4) ◽  
pp. 1834-1839

This study evaluated the land use/land cover (LULC) changes in Tuguegarao City and analyzed its impact on Land Surface Temperature (LST). It was carried out using Remote Sensing and Geographic Information System (GIS) techniques. Three Landsat TM and ETM+ images data were acquired for the years 1990, 2005 and 2016 from USGS Earth Explorer portal. ArcGIS software was used to determine the area statistics of the different land cover and to make the final LULC map. LST for the study area was taken from the thermal infrared band of the satellite images by converting the image digital number into degrees Kelvin using the LMin and LMax spectral radiance scaling factors. The largest areal change appeared in the built-up area with an increase of 1120.32 ha. However, this study detected higher LST in the crop land, grassland and barren land areas of the city rather than the built-up parts of the city which does not follow many of previous studies. The results of the study can be presented to the Local Government Unit so that they can draft appropriate laws for the betterment of the city specially that rapid urbanization and uncontrolled population growth may have extreme impact on the environment.


Author(s):  
A. Jamali ◽  
A. Abdul Rahman

Abstract. Environmental change monitoring in earth sciences needs land use land cover change (LULCC) modeling to investigate the impact of climate change phenomena such as droughts and floods on earth surface land cover. As land cover has a direct impact on Land Surface Temperature (LST), the Land cover mapping is an essential part of climate change modeling. In this paper, for land use land cover mapping (LULCM), image classification of Sentinel-1A Synthetic Aperture Radar (SAR) Ground Range Detected (GRD) data using two machine learning algorithms including Support Vector Machine (SVM) and Random Forest (RF) are implemented in R programming language and compared in terms of overall accuracy for image classification. Considering eight different scenarios defined in this research, RF and SVM classification methods show their best performance with overall accuracies of 90.81 and 92.09 percent respectively.


Author(s):  
Qijiao Xie ◽  
Qi Sun

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.


Climate ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 83
Author(s):  
Geofrey Gabiri ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Constanze Leemhuis ◽  
Roderick van der Linden ◽  
...  

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.


Author(s):  
Андрій Юрійович Шелестов ◽  
Алла Миколаївна Лавренюк ◽  
Богдан Ялкапович Яйлимов ◽  
Ганна Олексіївна Яйлимова

Ukraine is an associate member of the European Union and in the coming years it is expected that all data and services already used by EU countries will be available to Ukraine. The lack of quality national products for assessing the development and planning of urban growth makes it impossible to assess the impact of cities on the environment and human health. The first steps to create such products for the cities of Ukraine were initiated within the European project "SMart URBan Solutions for air quality, disasters and city growth" (SMURBS), in which specialists from the Space Research Institute of NAS of Ukraine and SSA of Ukraine received the first city atlas for the Kyiv city, which was similar to the European one. However, the resulting product had significantly fewer types of land use than the European one and therefore the question of improving the developed technology arose. The main purpose of the work is to analyze the existing technology of European service Urban Atlas creation and its improvement by developing a unified algorithm for building an urban atlas using all available open geospatial and satellite data for the cities of Ukraine. The development of such technology is based on our own technology for classifying satellite time series with a spatial resolution of 10 meters to build a land cover map, as well as an algorithm for unifying open geospatial data to urban atlases Copernicus. The technology of construction of the city atlas developed in work, based on the intellectual model of classification of a land cover, can be extended to other cities of Ukraine. In the future, the creation of such a product on the basis of data for different years will allow to assess changes in land use and make a forecast for further urban expansion. The proposed information technology for constructing the city atlas will be useful for assessing the dynamics of urban growth and closely related social and economic indicators of their development. Based on it, it is also possible to assess indicators of achieving the goals of sustainable development, such as 11.3.1 "The ratio of land consumption and population growth." The study shows that the city atlas obtained for the Kyiv city has a high level of quality and has comparable land use classes with European products. It indicates that such a product can be used in government decision-making services.


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