scholarly journals Quantifying the impact of land cover changes on hydrological extremes in India

2020 ◽  
Author(s):  
Shaini Naha ◽  
Miguel A. Rico-Ramirez ◽  
Rafael Rosolem
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Land Surface ◽  
Distributed Model ◽  
Model Parameters ◽  
Land Cover Changes ◽  
Area Index ◽  
Mahanadi River ◽  
The Impact

Abstract. Several research studies have addressed the effects of future climate changes on the hydrological regime of Mahanadi river basin located in eastern part of India. However, studies investigating the effects of future land cover changes on hydrology are limited owing to the lack of availability of projected land cover scenarios. Our study investigates how the hydrology of Mahanadi river basin would respond to the current and future land cover scenarios under a large-scale hydrological modelling framework. Both historical and future land cover scenarios from the recently released, Land use Harmonisation (LUH2) project for CMIP6, indicates cropland and forest are the major land cover types in the basin with a noticeable increase in the cropland (23.3 %) at the expense of forest (22.65 %) by the end of year 2100 compared to the baseline year, 2005. A physically semi-distributed model, the Variable Infiltration Capacity has been set up and implemented over the Mahanadi river basin system for the time period 1990–2010. The uncertain model parameters were subjected to Sensitivity Analysis and calibrated within a Monte Carlo framework. The best set of calibrated models obtained is used in conjunction with the harmonized set of present and future land use scenarios from LUH2 at 25 km by 25 km resolution to generate an ensemble of model simulations that captures a range of plausible impacts of land cover changes on discharge and other hydrological components of the basin. Overall, model simulation results indicate an increase in the extreme flows (i.e., 95th percentile or higher) in the range of 0.12 to 21 % at multiple subcatchments within the basin. This increase can be attributed to the direct conversion of forested areas to agriculture (on the order of 30,000 km2) that has reduced the Leaf Area Index and subsequently reduces the Evapotranspiration (ET). These changes ultimately affect other water balance components at the land surface, resulting in an increase in surface runoff and baseflow, respectively.

scholarly journals Quantifying the impact of land cover changes on hydrological responses in India

2021 ◽  
Author(s):  
Shaini Naha ◽  
Miguel A. Rico-Ramirez ◽  
Rafael Rosolem
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Distributed Model ◽  
Model Parameters ◽  
Area Index ◽  
Mahanadi River ◽  
Extreme Flows ◽  
Hydrological Responses ◽  
The Impact

Abstract. The objective of this study is to assess the impacts of Land Use Land Cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) within a Monte Carlo Framework to generate behavioural models for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released, Land use Harmonisation (LUH2) to generate hydrological predictions and related uncertainties from behavioural model parameterisation. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (on the order of 30,000 km2) reduces the Leaf Area Index and which subsequently reduces the Evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios, for instance uncertainty in far future scenario ranges from 17 to 210 cumecs across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in LULC at the catchment scale and suggests that model parameterisation represents an uncertainty, which should be accounted for in the land-use change impact assessment.

scholarly journals Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India

2021 ◽  
Vol 25 (12) ◽  
pp. 6339-6357
Author(s):  
Shaini Naha ◽  
Miguel Angel Rico-Ramirez ◽  
Rafael Rosolem
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
River Basin ◽  
Model Parameters ◽  
Area Index ◽  
Mahanadi River ◽  
Extreme Flows ◽  
Hydrological Responses ◽  
Model Parameterization

Abstract. The objective of this study is to assess the impacts of land cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models, through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) model, within a Monte Carlo framework to generate behavioural models that can yield equally good or acceptable model performances for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released Land-Use Harmonization version 2 (LUH2) dataset to generate hydrological predictions and related uncertainties from behavioural model parameterization. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 % to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (of the order of 30 000 km2) reduces the leaf area index, which subsequently reduces the evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios; for instance, uncertainty in scenario labelled “Far Future” ranges from 17 to 210 m3 s−1 across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in land use/land cover (LULC) at the catchment scale and suggests that model parameterization represents an uncertainty which should be accounted for in the land use change impact assessment.

scholarly journals Land Use and Land Cover Changes and Their Effect on the Flow Regime in the Upstream Dong Nai River Basin, Vietnam

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1206 ◽  
Author(s):  
Nguyen Truong ◽  
Hong Nguyen ◽  
Akihiko Kondoh
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flow Regime ◽  
River Basin ◽  
Vegetation Index ◽  
Secondary Forest ◽  
Spatial Scales ◽  
Small Scale ◽  
Land Cover Changes ◽  
The Impact

The upstream Dong Nai River Basin is located in the country’s key economic development region and its water resources are a key component of sustainable regional development. The objective of this study was to assess the impact of land use and land cover changes (LULCC) on the flow regime in this tropical forest basin using a flow–duration curve analysis that has been widely used in Japan. This study combined two different temporal and spatial scales of satellite data, Landsat and Global Inventory Modeling, and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) to analyze LUCC. Results from the land cover classification of five Landsat images between 1973 and 2014 indicated that the forest area decreased significantly in the period of 1994 to 2005 due to population growth, leading to land conversion for agriculture. Furthermore, secular changes in the annual GIMMS-NDVI data revealed that land cover changes occurred from 1996 and a large amount of forest was lost in 1999; however, due to the rapid regrowth of secondary forest of tropical forests and the development of the crop, the vegetation recovered shortly afterwards in 2000 before decreasing again after 2004. Following large-scale deforestation, the total discharge, maximum flow, and the plentiful, ordinary, low, and small-scale runoff increased sharply and decreased thereafter because of vegetation regrowth.

Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh

2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Surface Temperatures ◽  
Land Surface Temperatures
Sign in / Sign up

Export Citation Format

Share Document