Large decrease in streamflow and sediment load of Qinghai–Tibetan Plateau driven by future climate change: A case study in Lhasa River Basin

Tian, Peipei; Lu, Hongwei; Feng, Wei; Guan, Yanlong; Xue, Ying

doi:10.1016/j.catena.2019.104340

Cited by 139 publications

(48 citation statements)

References 45 publications

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“…Glaciers are a uniquely drought resilient source of water, which may pose an important but underappreciated role in protecting downstream populations from the worst effects of droughts 44 . Glacial meltwater is also a source recharging river headwaters and downstream runoff in the QTP 45 , 46 . Previous studies showed that the runoff from headwater area of the QTP would be rising in future decades 47 , 48 , while the downstream precipitation was decreasing in the surrounding areas.…”

Section: Discussionmentioning

confidence: 99%

Drought characteristics and its elevation dependence in the Qinghai–Tibet plateau during the last half-century

Feng

Yao

et al. 2020

Sci Rep

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152

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Associated with global warming, drought has destructive influences on agriculture and ecosystems, especially in the fragile Qinghai-Tibet Plateau (QTP). This study investigated spatial-temporal patterns of meteorological drought in the QTP and its surrounding areas and made an attempt to explore the relationship between drought conditions and elevation. Robust monitoring data from 274 meteorological stations during 1970-2017 were analyzed using the Sen's slope method, Mann-Kendall trend test and rescaled range analysis. Results revealed that under the wetting trend in the QTP, Standardized Precipitation Evapotranspiration Index (SPEI) increased of maximum 0.012/year in spring. Moreover, severe drought frequency in winter and future drought risk in summer also showed an increasing trend. Wetter trends were positively correlated with elevation, with a key point being 4,000 m where the change trend above 4,000 m was about 6.3 times of that below 4,000 m in study area. The difference of drought severities between SPEI in the QTP and its surrounding areas has increased from − 0.19 in 1970 to 0.38 in 2017 and kept growing in future. Drought is one of the most widespread and costly natural disasters 1 , which can endanger the production of agriculture and animal husbandry, worsen the ecological environment, and even expose human to the risk of disease 2,3. Previous studies have suggested that under global warming, the percentage of dry areas in the world has increased by approximately 1.74% per decade during 1950-2008 4,5. With an average elevation above 4,000 m and an area of 200,000 square kilometers, the Qinghai-Tibet Plateau (QTP) is the source of major rivers in Asia 6-8. It is extremely vulnerable to global change, and easily suffers from drought. The drought herein will have profound impacts on the neighboring regions. Therefore, a comprehensive understanding of drought characteristics in the QTP is of great importance. Many studies on spatiotemporal characteristics of drought in the QTP and its surrounding areas have been conducted, mainly concluded that the QTP has become warmer and wetter in the past decades, especially in the vast northwestern QTP 5-7,9-13. Additionally, Gao et al. 8 analyzed the aridity changes using P/PET ratio in recent 30 years based on 83 stations, and found that the eastern QTP was becoming drier and the aridity change pattern was significantly correlated with precipitation, sunshine duration and diurnal temperature range. Liang et al. 14 investigated 74 stations in the QTP during 1980-2014 and found that the drought pattern exhibited obvious inter-decadal variation and severe drought mainly occurred before the 1990s. Yang et al. 15 forecasted an increasing drought trend in southwest China (including Yunnan Province) but an increasing wetting trend for the QTP based on simulation of Global Climate Models (GCM) taken from the Coupled Model Intercomparison Project Phase 5 (CMIP5) framework. Other studies have addressed the seasonal drought evolution in the QTP. Some concluded that the dro...

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Section: Discussionmentioning

confidence: 99%

Drought characteristics and its elevation dependence in the Qinghai–Tibet plateau during the last half-century

Feng

Yao

et al. 2020

Sci Rep

Self Cite

152

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“…Where, A s and β denotes cumulative catchment area (m 2 ) and define slope angle, respectively. The phenomenon of climate change and several human induced activities are considered the two major drivers flow pattern in a basin area and impacted on hydrological factors (Feng et al, 2020;Tian et al, 2020).…”

Section: Land Subsidence Conditioning Factors (Lscfs)mentioning

confidence: 99%

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

et al. 2021

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The optimal prediction of land subsidence (LS) is very much difficult because of limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning and behavior of LS. Thus, due to the lack of LS susceptibility maps it is almost impossible to identify LS prone areas and as a result it influences severe economic and human losses. Hence, preparation of LS susceptibility mapping (LSSM) can help to prevent natural and human catastrophes and reduce the economic damages significantly. Machine learning (ML) techniques are becoming increasingly proficient in modeling purpose of such kinds of occurrences and they are increasing used for LSSM. This study compares the performances of single and hybrid ML models to preparation of LSSM for future prediction of performance analysis. In this study, the spatial prediction of LS was assessed using four ML models of maximum entropy (MaxEnt), general linear model (GLM), artificial neural network (ANN) and support vector machine (SVM). Alongside, the possible numbers of novel ensemble models were integrated through the aforementioned four ML models for optimal analysis of LSSM. An inventory LS map was prepared based on the previous occurrences of LS points and the dataset were divvied into 70:30 ratios for training and validating of the modeling process. To identify the robust and best LSSMs, receiver operating characteristic-area under curve (ROC-AUC) curve was employed. The ROC-AUC result indicated that ANN model gives the highest ROC-AUC (0.924) in training accuracy. The highest AUC (0.823) of the LSSMs was determined based on validation datasets identified by SVM followed by ANN-SVM (0.812).

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“…As well as this, other difficulties such as the non-linearity of the problem have driven many scholars to improve the flexibility of intelligent models. As discussed by many scholars, along with well-known models (e.g., decision-making [6][7][8][9]), the artificial intelligence techniques have provided a high capability in the estimation of non-linear and intricate parameters [10][11][12]. Plenty of scientific efforts (e.g., concerning environmental subjects [13][14][15][16][17][18][19][20][21][22][23], gas consumption modeling [24,25], sustainable developments [26], pan evaporation and soil precipitation simulation [26][27][28][29][30][31], energy-related estimations [32][33][34][35][36][37][38][39], water supply assessment [16,[40][41][42][43][44][45][46][47][48][49], computer v...…”

Section: Introductionmentioning

confidence: 99%

Synthesizing Multi-Layer Perceptron Network with Ant Lion Biogeography-Based Dragonfly Algorithm Evolutionary Strategy Invasive Weed and League Champion Optimization Hybrid Algorithms in Predicting Heating Load in Residential Buildings

Moayedi

Mosavi

2021

Sustainability

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The significance of accurate heating load (HL) approximation is the primary motivation of this research to distinguish the most efficient predictive model among several neural-metaheuristic models. The proposed models are formulated through synthesizing a multi-layer perceptron network (MLP) with ant lion optimization (ALO), biogeography-based optimization (BBO), the dragonfly algorithm (DA), evolutionary strategy (ES), invasive weed optimization (IWO), and league champion optimization (LCA) hybrid algorithms. Each ensemble is optimized in terms of the operating population. Accordingly, the ALO-MLP, BBO-MLP, DA-MLP, ES-MLP, IWO-MLP, and LCA-MLP presented their best performance for population sizes of 350, 400, 200, 500, 50, and 300, respectively. The comparison was carried out by implementing a ranking system. Based on the obtained overall scores (OSs), the BBO (OS = 36) featured as the most capable optimization technique, followed by ALO (OS = 27) and ES (OS = 20). Due to the efficient performance of these algorithms, the corresponding MLPs can be promising substitutes for traditional methods used for HL analysis.

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Large decrease in streamflow and sediment load of Qinghai–Tibetan Plateau driven by future climate change: A case study in Lhasa River Basin

Cited by 139 publications

References 45 publications

Drought characteristics and its elevation dependence in the Qinghai–Tibet plateau during the last half-century

Drought characteristics and its elevation dependence in the Qinghai–Tibet plateau during the last half-century

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

Synthesizing Multi-Layer Perceptron Network with Ant Lion Biogeography-Based Dragonfly Algorithm Evolutionary Strategy Invasive Weed and League Champion Optimization Hybrid Algorithms in Predicting Heating Load in Residential Buildings

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