The impact of using different probability representations in application of equidistant quantile matching for bias adjustment of daily precipitation over the Daqing River Basin, North China

Author(s):  
Lv Mingcong ◽  
Gao Xueping ◽  
Liu Yinzhu ◽  
Ju Wenhui ◽  
Sun Bowen ◽  
...  
2010 ◽  
Vol 62 (4) ◽  
pp. 783-791 ◽  
Author(s):  
Jing Fan ◽  
Fei Tian ◽  
Yonghui Yang ◽  
Shumin Han ◽  
Guoyu Qiu

Runoff in North China has been dramatically declining in recent decades. Although climate change and human activity have been recognized as the primary driving factors, the magnitude of impact of each of the above factors on runoff decline is still not entirely clear. In this study, Mian River Basin (a watershed that is heavily influenced by human activity) was used as a proxy to quantify the contributions of human and climate to runoff decline in North China. SWAT (Soil and Water Assessment Tool) model was used to isolate the possible impacts of man and climate. SWAT simulations suggest that while climate change accounts for only 23.89% of total decline in mean annual runoff, human activity accounts for the larger 76.11% in the basin. The gap between the simulated and measured runoff has been widening since 1978, which can only be explained in terms of increasing human activity in the region. Furthermore, comparisons of similar annual precipitation in 3 dry-years and 3 wet-years representing hydrological processes in the 1970s, 1980s, and 1990s were used to isolate the magnitude of runoff decline under similar annual precipitations. The results clearly show that human activity, rather than climate, is the main driving factor of runoff decline in the basin.


2013 ◽  
Vol 28 (23) ◽  
pp. 5755-5768 ◽  
Author(s):  
Aizhong Ye ◽  
Qingyun Duan ◽  
Wei Chu ◽  
Jing Xu ◽  
Yuna Mao

1993 ◽  
Vol 28 (1) ◽  
pp. 83-110 ◽  
Author(s):  
Richard E. Farrell ◽  
Jae E. Yang ◽  
P. Ming Huang ◽  
Wen K. Liaw

Abstract Porewater samples from the upper Qu’Appelle River basin in Saskatchewan, Canada, were analyzed to obtain metal, inorganic ligand and amino add profiles. These data were used to compute the aqueous speciation of the metals in each porewater using the computer program GEOCHEM-PC. The porewaters were classified as slightly to moderately saline. Metal concentrations reflected both the geology of the drainage basin and the impact of anthropogenic activities. Whereas K and Na were present almost entirely as the free aquo ions, carbonate equilibria dominated the speciation of Ca. Mg and Mn (the predominant metal ligand species were of the type MCO3 (s). MCO30. and MHCO3+). Trace metal concentrations were generally within the ranges reported for non-polluted freshwater systems. Whereas the speciation of the trace metals Cr(III) and Co(II) was dominated by carbonate equilibria, Hg(II)-, Zn(II)- and Fe(II)-speciation was dominated by hydroxy-metal complexes of the type M(OH)+ and M(OH)2°. The speciation of Fe(III) was dominated by Fe(OH)3 (s). In porewaters with high chloride concentrations (> 2 mM), however, significant amounts of Hg(II) were bound as HgCl20 and HgClOH0. The aqueous speciation of Al was dominated by Al(OH)4− and Al2Si2O4(OH)6 (s). Total concentrations of dissolved free amino acids varied from 15.21 to 25.17 umole L−1. The most important metal scavenging amino acids were histidine (due to high stability constants for the metal-histidine complexes) and tryptophan (due to its relatively high concentration in the porewaters. i.e., 5.96 to 7.73 umole L−1). Secondary concentrations of various trace metal-amino add complexes were computed for all the porewaters, but metal-amino acid complexes dominated the speciation of Cu(II) in all the porewaters and Ni(II) in two of the porewaters.


1982 ◽  
Vol 14 (4-5) ◽  
pp. 245-252 ◽  
Author(s):  
C S Sinnott ◽  
D G Jamieson

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.


PAMM ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Gerson C. Kroiz ◽  
Reetam Majumder ◽  
Matthias K. Gobbert ◽  
Nagaraj K. Neerchal ◽  
Kel Markert ◽  
...  

Author(s):  
Weiqi Xu ◽  
Chun Chen ◽  
Yanmei Qiu ◽  
Conghui Xie ◽  
Yunle Chen ◽  
...  

Organic aerosol (OA), a large fraction of fine particles, has a large impact on climate radiative forcing and human health, and the impact depends strongly on size distributions. Here we...


Author(s):  
Philip E. Bett ◽  
Gill M. Martin ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Hazel E. Thornton ◽  
...  

AbstractSeasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.


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