scholarly journals Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China

2021 ◽  
Author(s):  
Xu Chen ◽  
Ruiguang Han ◽  
Ping Feng ◽  
Yongjie Wang
2021 ◽  
Author(s):  
Xu Chen ◽  
Ruiguang Han ◽  
Yongjie Wang

Abstract Drought can be impacted by both climate change and land use change in different ways. Thus, in order to predict future drought conditions, hydrological simulations as an ideal means, can be used to account for both projected climate change and projected land use change. In this study, projected climate and land use changes were integrated with the SWAT (Soil and Water Assessment Tool) model to estimate the combined impact of climate and land use projections on hydrological droughts in the Luanhe River basin. We presented that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of model parameters. Following the calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine Global Climate Models (GCMs) based on the CMIP5, corresponding to three different representative concentration pathways (RCP 2.6, RCP 4.5 and 8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early-century, mid-century and late-century, respectively, and the land use predicted by CA-Markov model in the same future periods. Hydrological droughts were quantified using the Standardized Runoff Index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except the 2080s under the RCP2.6 emission scenario). Under the RCP8.5 emission scenario, the probability of severe drought or above occurring in the 2080s increased, the duration prolonged and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe river in the 2020s and upper reaches of the Luanhe river in the 2080s, were more likely to suffer extreme drought events. And under the RCP8.5 scenario, the middle and lower Luanhe river in the 2080s, were more likely to suffer these conditions.


Author(s):  
Xin Zhang ◽  
Lin Zhou ◽  
Yuqi Liu

Changes in landscape patterns in a river basin play a crucial role in the change on load of non-point source pollution. The spatial distribution of various land use types affects the transmission of non-point source pollutants on the basis of source-sink theory in landscape ecology. Jiulong River basin in southeast of China was selected as the study area in this paper. Aiming to analyze the correlation between changing landscape patterns and load of non-point source pollution in this area, traditional landscape metrics and the improved location-weighted landscape contrast index based on the minimum hydrological response unit (HRULCI) were applied in this study, in combination with remote sensing and geographic information system (GIS) technique. The results of the landscape metrics showed the enhanced fragmentation extent and the decreasing polymerization degree of the overall landscape in the watershed. High values of HRULCI were concentrated in cultivated land, while low HRULCI values mostly appeared in forestland, indicating that cultivated land substantially enhanced non-point source pollution, while forestland inhibited the pollution process.


Author(s):  
Jiren Xu ◽  
Fabrice G. Renaud ◽  
Brian Barrett

AbstractA more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale.


10.5109/27370 ◽  
2013 ◽  
Vol 58 (2) ◽  
pp. 377-387
Author(s):  
Yanna Xiong ◽  
Guoqiang Wang ◽  
Yanguo Teng ◽  
Kyoichi Otsuki

2008 ◽  
Vol 2 (No. 3) ◽  
pp. 77-84
Author(s):  
R. Pavelková Chmelová ◽  
B. Šarapatka ◽  
M. Dumbrovský ◽  
P. Pavka

In this paper, the authors summarise the land use changes in the upper reaches of the Krupá river catchment, which is a left tributary of the Morava River. During last 70 years, the catchment was exposed to many important historical events that have been inscribed in the physique of the landscape in a very interesting way. The land use changes, which occurred during the last eight decades in the subcatchment of the Krupá river basin, have been analysed using historical maps, cadastral maps, and both historical and recent aerial photographs of the area. The next step is to estimate, through the CN method and DesQ hydrological model, how the runoff processes in the Krupá River catchment could be influenced by the land use changes.


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