scholarly journals Hydrological Response of the Imphal River on the Impact of Landuse/ Landcover and Rainfall Patterns

2020 ◽  
Vol 66 (2) ◽  
pp. 126-135
Author(s):  
Kh. Pradipkumar Singh ◽  
◽  
Priyalina Sapam ◽  

The river regime is one of the important parameters in studying the physical attributes in a region. The influence of a river passing in a region is immense. The nature of the stream reflects the natural and cultural set up of the surrounding areas. For instance soil factors, Land use/Land cover and vegetation, habitat, settlements, etc. Everywhere land use/ land cover is often altered during the process of economic and social development and eventually, the morphology and structure of river systems are unconsciously or consciously influenced along with the land-use change. The changes in land use/ land cover have a large amount of impact on the nature of runoff and associated hydrological characteristics. Availability of remotely sensed data has made convenient and accurate to map and monitor the Spatio-temporal variation of land use/ land cover at regional or local scales. The present paper highlights the changing of land use pattern in the Imphal River catchment. To identify the changes, Landsat 5 TM and Landsat 7 ETM+ obtained in 2005 and 2016 have been used and categorize the images into 16 major land use/ land cover. It has been found that over the periods both rural and urban built-up area has increased more than 24 Km2 and decreased in forests cover area by more than 113 Km2 . Further, the study also focused on the rainfallrunoff response through regression analysis. The integration of the analyses demonstrates the effect of land use/ land cover change on discharge characteristics of the study area.

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.


2012 ◽  
Vol 49 (5) ◽  
pp. 980-989 ◽  
Author(s):  
S. Bajocco ◽  
A. De Angelis ◽  
L. Perini ◽  
A. Ferrara ◽  
L. Salvati

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 (4) ◽  
pp. 1150-1164
Author(s):  
Swapnali Barman ◽  
Rajib Kumar Bhattacharjya

Abstract The River Subansiri, one of the largest tributaries of the Brahmaputra, makes a significant contribution towards the discharge at its confluence with the Brahmaputra. This study aims to investigate an appropriate model to predict the future flow scenario of the river Subansiri. Two models have been developed. The first model is an artificial neural network (ANN)-based rainfall-runoff model where rainfall has been considered as the input. The future rainfall of the basin is calculated using a multiple non-linear regression-based statistical downscaling technique. The proposed second model is a hybrid model developed using ANN and the Soil Conservation Service (SCS) curve number (CN) method. In this model, both rainfall and land use/land cover have been incorporated as the inputs. The ANN models were run using time series analysis and the method selected is the non-linear autoregressive model with exogenous inputs. Using Sen's slope values, the future trend of rainfall and runoff over the basin have been analyzed. The results showed that the hybrid model outperformed the simple ANN model. The ANN-SCS-based hybrid model has been run for different land use/land cover scenarios to study the future flow scenario of the River Subansiri.


2011 ◽  
Vol 31 (3) ◽  
pp. 1166-1172 ◽  
Author(s):  
Fatih Evrendilek ◽  
Suha Berberoglu ◽  
Nusret Karakaya ◽  
Ahmet Cilek ◽  
Guler Aslan ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document