Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change

Wang, Qianfeng; Qi, Junyu; Wu, Huan; Zeng, Yuehua; Shui, Wei; Zeng, Jiali; Zhang, Xuesong

doi:10.1016/j.catena.2020.104767

Cited by 58 publications

(27 citation statements)

References 63 publications

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“…Except for surface runoff, changing trends in annual stream flow, water yield, and subsurface runoff were opposite to respective nitrate loadings for both models. The downward trends of stream flow, water yield, and subsurface runoff were caused by the increasing ET in the UMRB (Wang et al, 2020), while the upward trends of riverine nitrate flux, total terrestrial nitrate loading, and subsurface nitrate loading were due to increased nitrate concentration in soil profile caused by accelerated mineralization and nitrification rates under future warmer conditions (Dai et al, 2020). For the annual surface runoff, it had the similar changing trends to the annual surface nitrate loading projected by both models with the original SWAT model having decreasing trends in surface runoff and surface nitrate loading, and SWAT-FT having insignificant changing trends (P-value >0.05; Fig.…”

Section: Relation Between Nitrate Loading and Water Flowmentioning

confidence: 99%

“…were simulated by a CENTURY-based C/N cycling module which was recently incorporated into the SWAT model by Zhang et al (2013). The module has proven to simulate soil C/N transformation and C/N loading/emissions from agricultural soils better than the original SWAT's soil biogeochemistry module (Qi et al, 2020;Yang et al, 2017;Zhang, 2018;Zhang et al, 2013). The CENTURY-based C/N cycling module separates the soil organic matter and residue into five pools, including structural litter, metabolic litter, microbial biomass, and slow and passive humus, and simulates addition, decomposition, transformation, and removal of each SOM-residue pool present in surface and subsurface soil layers (Zhang et al, 2013).…”

Section: Nitrate Cycling Coupled With Soil Hydrology-soil Biogeochemical Processesmentioning

confidence: 99%

“…previously developed SWAT project for the UMRB has been successfully tested for water quantity and quality simulations under ungauged conditions (Qi et al, 2019a(Qi et al, , 2019c(Qi et al, , 2020Srinivasan et al, 2010) 2). The future projection dataset has been corrected with observed data using the bias-correction and spatial-downscaling approach (Yang et al, 2019).…”

Section: Model Setup and Data Collection-amentioning

confidence: 99%

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Nitrate loading projection is sensitive to freeze-thaw cycle representation

Wang

Qi²,

Li³

et al. 2020

Water Research

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Section: Relation Between Nitrate Loading and Water Flowmentioning

confidence: 99%

Section: Nitrate Cycling Coupled With Soil Hydrology-soil Biogeochemical Processesmentioning

confidence: 99%

Section: Model Setup and Data Collection-amentioning

confidence: 99%

See 1 more Smart Citation

Nitrate loading projection is sensitive to freeze-thaw cycle representation

Wang

Qi²,

Li³

et al. 2020

Water Research

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“…All daily SPEI datasets including data and their description at 427 observed meteorological stations are provided open access via figshare (Wang et al, 2020c), available at https://doi.org/10.6084/m9.figshare.12568280. This depository includes the five files of the daily SPEI data with five scales (30 d about 1 month, 90 d about 3 months, 180 d about 6 months, 360 d about 12 months, 720 d about 24 months) and station information for 427 meteorological stations.…”

Section: Data Availabilitymentioning

confidence: 99%

A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018

Wang

Zeng

et al. 2021

Earth Syst. Sci. Data

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120

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Abstract. The monthly standardized precipitation evapotranspiration index (SPEI) can be used to monitor and assess drought characteristics with 1-month or longer drought duration. Based on data from 1961 to 2018 at 427 meteorological stations across mainland China, we developed a daily SPEI dataset to overcome the shortcoming of the coarse temporal scale of monthly SPEI. Our dataset not only can be used to identify the start and end dates of drought events, but also can be used to investigate the meteorological, agricultural, hydrological, and socioeconomic droughts with a different timescales. In the present study, the SPEI data with 3-month (about 90 d) timescale were taken as a demonstration example to analyze spatial distribution and temporal changes in drought conditions for mainland China. The SPEI data with a 3-month (about 90 d) timescale showed no obvious intensifying trends in terms of severity, duration, and frequency of drought events from 1961 to 2018. Our drought dataset serves as a unique resource with daily resolution to a variety of research communities including meteorology, geography, and natural hazard studies. The daily SPEI dataset developed is free, open, and publicly available from this study. The dataset with daily SPEI is publicly available via the figshare portal (Wang et al., 2020c), with https://doi.org/10.6084/m9.figshare.12568280.Highlights. A multi-scale daily SPEI dataset was developed across mainland China from 1961 to 2018. The daily SPEI dataset can be used to identify the start and end days of the drought event. The developed daily SPEI dataset in this study is free, open, and publicly available.

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“…Although the rapid urbanization of China has promoted economic growth, it has also led to negative environmental consequences. According to the Fifth Assessment Report of the IPCC [1], the global average land surface temperature (LST) increased by 0.85°C from 1880 to 2012, with global warming [2] as the defining climatic trait of this period [3,4].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China

Han

Liu

et al. 2020

Complexity

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Intensified due to rapid urbanization and global warming-induced high temperature extremes, the urban heat island effect has become a major environmental concern for urban residents. Scientific methods used to calculate the urban heat island intensity (UHII) and its alleviation have become urgent requirements for urban development. This study is carried out in Zhongshan District, Dalian City, which has a total area of 43.85 km2 and a 27.5 km-long coastline. The mono-window algorithm was used to retrieve the land surface temperatures (LSTs), employing Landsat remote sensing images, meteorological data, and building data from 2003, 2008, 2013, and 2019. In addition, the district was divided into local climate zones (LCZs) based on the estimated intensities and spatiotemporal variations of the heat island effect. The results show that, from 2003 to 2019, LCZs A and D shrank by 3.225 km2 and 0.395 km2, respectively, whereas LCZs B, C, and 1–6 expanded by 0.932 km2, 0.632 km2, and 2.056 km2, respectively. During this period, the maximum and minimum LSTs in Zhongshan increased by 1.365°C and 1.104°C, respectively. The LST and UHII levels of all LCZs peaked in 2019. The average LSTs of LCZs A–C increased by 1.610°C, 0.880°C, and 3.830°C, respectively, and those of LCZs 1–6 increased by 2°C–4°C. The UHIIs of LCZs A, C, and D increased by 0.730, 2.950, and 0.344, respectively, and those of LCZs 1–6 increased from 1.370–2.977 to 3.744–5.379. Overall, the regions with high LSTs are spatiotemporally correlated with high building densities. In this study, the land cover was then classified into four types (LCZs A–D) using visual interpretation and object-oriented classification, including forested land, low vegetation, bare ground, and water. Besides, the buildings were categorized as LCZs 1–6, which, respectively, represented low-density low-rises buildings, low-density high-rises buildings, low-density super high-rises buildings, high-density low-rises buildings, high-density high-rises buildings, and high-density super high-rises buildings.

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Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change

Cited by 58 publications

References 63 publications

Nitrate loading projection is sensitive to freeze-thaw cycle representation

Nitrate loading projection is sensitive to freeze-thaw cycle representation

A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018

Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China

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