scholarly journals The Influence of Rainfall and Land Use/Land Cover Changes on River Discharge Variability in the Mountainous Catchment of the Bagmati River

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2444 ◽  
Author(s):  
Dinesh Tuladhar ◽  
Ashraf Dewan ◽  
Michael Kuhn ◽  
Robert J. Corner
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Discharge ◽  
Forest Cover ◽  
Agricultural Land ◽  
Strong Association ◽  
Land Use Land Cover ◽  
Discharge Data ◽  
Bagmati River

Changes in rainfall and land use/land cover (LULC) can influence river discharge from a catchment in many ways. Homogenized river discharge data from three stations and average rainfall records, interpolated from 13 stations, were examined for long-term trends and decadal variations (1970–2017) in the headwater, upper and middle catchments of the Bagmati River. LULC changes over five decades were quantified using multitemporal Landsat images. Mann–Kendall tests on annual time series showed a significant decrease in river discharge (0.61% per year) from the entire Bagmati catchment, although the decrease in rainfall was statistically insignificant. However, declines in river discharge and rainfall were both significant in upper catchment. Decadal departures from long-term means support these trend results. Over tenfold growth in urban area and a decrease in agricultural land were observed in the upper catchment, while forest cover slightly increased in the entire catchment between 1975 and 2015. Correlation analysis showed a strong association between surface runoff, estimated using the curve number method, observed river discharge and rainfall in the upper catchment, while the relationship was weaker in the headwater catchment. These results were also supported by multiple regression analysis, suggesting that human activities together with climate change have contributed to river discharge changes in the Bagmati catchment.

scholarly journals Land use/land cover change assessment of Mohana watershed (Far-Western Nepal) using GIS and remote sensing

2021 ◽  
Vol 6 (3) ◽  
pp. 320-328
Author(s):  
Suraj Prasad Bist ◽  
Rabindra Adhikari ◽  
Raju Raj Regmi ◽  
Rajan Subedi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land ◽  
Gis And Remote Sensing

The present study was conducted in the Mohana watershed of Far-western Nepal to assess land use land cover change. The study has used ArcGIS and three Landsat images - Landsat TM (1999), Landsat ETM+ (2009), and Landsat OLI (2019) – to analyze land use the land cover change of the watershed. The change matrix technique was used for change detection analysis. The study area was classified into five classes; forest, agriculture, built-up, water bodies, and barren lands. The study has found that among the five identified classes forest and build-up increased positively from 45.40 % to 51.51 % - forest cover and 11.26 % to 19. 85 % - build-up respectively. Similarly, agricultural land and water bodies initially increased but after 2009 both land cover areas decreased to 23.79 % and 0.73 % from 31.38 % and 0.97 % in 2009 respectively. Barren land decreased from 15.37% to 4.12% over the last 20 years. This study might support land-use planners and policymakers to adopt the best suitable land use management option for the Mohana watershed.

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

scholarly journals Ecosystem Service Values Changes in Response to Land-Use/Land-Cover Dynamics in Dry Afromontane Forest in Northern Ethiopia

2019 ◽  
Vol 16 (23) ◽  
pp. 4653 ◽  
Author(s):  
Negasi Solomon ◽  
Alcade C. Segnon ◽  
Emiru Birhane
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Ecosystem Service ◽  
Forest Cover ◽  
Northern Ethiopia ◽  
Land Use Land Cover ◽  
Afromontane Forest ◽  
Land Cover Dynamics ◽  
Dry Afromontane Forest

Despite their importance as sources of ecosystem services supporting the livelihoods of millions of people, forest ecosystems have been changing into other land use systems over the past decades across the world. While forest cover change dynamics have been widely documented in various ecological systems, how these changes affect ecosystem service values has received limited attention. In this study we assessed the impact of land-use/land-cover dynamics on ecosystem service values in dry Afromontane forest in Northern Ethiopia. We estimated ecosystem service values and their changes based on the benefit transfer method using land cover data of the years 1985, 2000, and 2016 with their corresponding locally valid value coefficients and from the Ecosystem service valuation database. The total ecosystem service values of the whole study area were about USD 16.6, 19.0, and 18.1 million in 1985, 2000, and 2016, respectively. The analyses indicated an increase in ecosystem service values from 1985 to 2000 and a decrease in ecosystem service values from 2000 to 2016. Similarly, the contribution of specific ecosystem services increased in the first study period and decreased in the second study period. The findings highlight how forest cover dynamics can be translated into changes in ecosystem service values in dry Afromontane forest ecosystems in Northern Ethiopia and showed how specific ecosystem services contributed to the observed trends. The findings also illustrated the temporal heterogeneity in the impacts of land-use/land-cover dynamics on values of ecosystem services. The findings can serve as crucial inputs for policy and strategy formulations for the sustainable use and management of forest resources and can also guide the allocation of limited resources among competing demands to safeguard the ecosystems that offer the best-valued services.

scholarly journals A Century of Forest Regrowth and Snow Loss Alters the Cooling Effect of Historical Land Use in the Upper Midwest

Ecosystems ◽  
2019 ◽  
Vol 23 (5) ◽  
pp. 1056-1074
Author(s):  
Bethany J. Blakely ◽  
Adrian V. Rocha ◽  
Jason S. McLachalan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Snow Cover ◽  
Forest Canopy ◽  
Forest Cover ◽  
Cooling Effect ◽  
Forest Regrowth ◽  
Historical Land Use ◽  
Over Time

AbstractAnthropogenic land use affects climate by altering the energy balance of the Earth’s surface. In temperate regions, cooling from increased albedo is a common result of historical land-use change. However, this albedo cooling effect is dependent mainly on the exposure of snow cover following forest canopy removal and may change over time due to simultaneous changes in both land cover and snow cover. In this paper, we combine modern remote sensing data and historical records, incorporating over 100 years of realized land use and climatic change into an empirical assessment of centennial-scale surface forcings in the Upper Midwestern USA. We show that, although increases in surface albedo cooled through strong negative shortwave forcings, those forcings were reduced over time by a combination of forest regrowth and snow-cover loss. Deforestation cooled strongly (− 5.3 Wm−2) and mainly in winter, while composition shift cooled less strongly (− 3.03 Wm−2) and mainly in summer. Combined, changes in albedo due to deforestation, shifts in species composition, and the return of historical forest cover resulted in − 2.81 Wm−2 of regional radiative cooling, 55% less than full deforestation. Forcings due to changing vegetation were further reduced by 0.32 Wm−2 of warming from a shortened snow-covered season and a thinning of seasonal snowpack. Our findings suggest that accounting for long-term changes in land cover and snow cover reduces the estimated cooling impact of deforestation, with implications for long-term land-use planning.

scholarly journals LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 231-237 ◽  
Author(s):  
S. A. Rahaman ◽  
S. Aruchamy ◽  
K. Balasubramani ◽  
R. Jegankumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Southern India ◽  
Vegetation Changes ◽  
Land Use Land Cover ◽  
Mountain Landscape ◽  
Semi Arid

Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

scholarly journals Classification of various land features using RISAT-1 dual polarimetric data

2014 ◽  
Vol XL-8 ◽  
pp. 833-837 ◽  
Author(s):  
V. N. Mishra ◽  
P. Kumar ◽  
D. K. Gupta ◽  
R. Prasad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Uttar Pradesh ◽  
Land Cover Classification ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Remotely Sensed Data ◽  
Sar Data ◽  
Land Cover Maps

Land use land cover classification is one of the widely used applications in the field of remote sensing. Accurate land use land cover maps derived from remotely sensed data is a requirement for analyzing many socio-ecological concerns. The present study investigates the capabilities of dual polarimetric C-band SAR data for land use land cover classification. The MRS mode level 1 product of RISAT-1 with dual polarization (HH & HV) covering a part of Varanasi district, Uttar Pradesh, India is analyzed for classifying various land features. In order to increase the amount of information in dual-polarized SAR data, a band HH + HV is introduced to make use of the original two polarizations. Transformed Divergence (TD) procedure for class separability analysis is performed to evaluate the quality of the statistics prior to image classification. For most of the class pairs the TD values are greater than 1.9 which indicates that the classes have good separability. Non-parametric classifier Support Vector Machine (SVM) is used to classify RISAT-1 data with optimized polarization combination into five land use land cover classes like urban land, agricultural land, fallow land, vegetation and water bodies. The overall classification accuracy achieved by SVM is 95.23 % with Kappa coefficient 0.9350.

scholarly journals Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

2019 ◽  
Vol 4 (6) ◽  
pp. 84-89 ◽  
Author(s):  
Aniekan Effiong Eyoh ◽  
Akwaowo Ekpa
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Analysis ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Land Use Land Cover ◽  
Positive Growth ◽  
Bare Land ◽  
Erdas Imagine

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.

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