The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye

doi:10.1016/j.jhydrol.2018.04.033

Cited by 14 publications

(6 citation statements)

References 62 publications

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“…It was noted by Bayazit (2015) that the impacts of climate change and anthropogenic activities on river basins and low-frequency climatic variability were the main reasons for non-stationarity. Milly et al (2015) stated that non-stationary conditions can come from local human activities (such as land use and land cover change, land drainage, dams, diversions, water withdrawals, and groundwater depletion) and anthropogenic climate change (ACC), whose influences are extensive, imperceptible, and growing (Shao et al, 2016(Shao et al, , 2018Wang et al, 2017;Zhu et al, 2018;Bai et al, 2019;Wang K. et al, 2019;Yu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

et al. 2020

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The Mann-Kendall (MK) statistical test has been widely applied in the trend detection of the hydrometeorological time series. Previous studies have mainly focused on the null hypothesis of "no trend" or the "Type I Error." However, few studies address the capability of the MK test to successfully recognize the trends. In some cases, especially when the trend test is jointly applied with hydropower station design, flood risk assessment, and water quality evaluation, the "Type II error" is equally important and should not be neglected. To cope with this problem, we carry out Monte Carlo simulations and the results indicate that in addition to the significance level and the sample length, the MK test power has a close relationship with the sample variance and the magnitude of the trend. For a given time series with fixed length, the power of the MK test increases as the slope increases and declines with increasing sample variance. A deterministic relationship between the slope and the standard deviation of the white noise that can be used for evaluating the power of the MK test has also been detected. Furthermore, we find that a positive autocorrelation contained in the time series will increase both the Type I and the Type II errors due to the enlargement of the variance in the MK statistics. Finally, we recommend that researchers slightly increase the significance level and lengthen the time series sample to improve the power of the MK test in future studies.

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Section: Introductionmentioning

confidence: 99%

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

et al. 2020

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“…In arid or semiarid settings, evaporation directly from soil can account for more than half of the total evapotranspiration and therefore critical to its understanding (Huxman et al, ). Even though decades of research have improved our understanding of evaporation at the laboratory and regional scales (Brutsaert, ; Budagovskij, ; Merta et al, ; Morton, ; Shao et al, ; Shuttleworth, ; Swenson & Lawrence, ), many knowledge gaps still exist in the current science on how the shallow subsurface interacts with the atmosphere during evaporation. Comprehensive understanding of the mechanisms involved in the atmosphere‐subsurface interaction is significant to some relevant studies, such as the greenhouse gases emission (Pourbakhtiar et al, ) and the remediation of contaminated shallow soil (Weaver & Tillman, ).…”

Section: Introductionmentioning

confidence: 99%

“…This approach focuses on the entire evaporation amount while oversimplifing the evaporation processes. Another theoretical approach is to use the Penman‐Monteith equation alone to calculate evaporation in large‐scale hydrological model on the precondition that all the parameters are known (Shao et al, ). Other experimental and modeling contributions at smaller scales include those by Lehmann et al (), Shahraeeni et al (), and Haghighi et al ().…”

Section: Introductionmentioning

confidence: 99%

Experimental and Numerical Study of Evaporation From Wavy Surfaces by Coupling Free Flow and Porous Media Flow

Gao

Davarzani

Helmig

et al. 2018

Water Resources Research

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The macroscale roughness of the soil surface has significant influences on the mass/energy interactions between the subsurface and the atmosphere during evaporation. However, most previous works only consider evaporation behavior from flat surfaces. Based on experimental and numerical approaches, the goal of this work is to provide a framework for the understanding of the mechanisms of evaporation from irregular soil surfaces at representative elementary volume scale. A coupling free flow‐porous media flow model was developed to describe evaporation under nonisothermal conditions. For simplicity, sinusoidal‐type wavy surfaces were considered. To validate this modeling approach, an experiment using an open‐ended wind tunnel and soil tank was conducted. The experimental system was instrumented with various environmental sensors to continuously collect atmospheric and subsurface data. Results demonstrate that the surface roughness directly affects both atmospheric and diffusion‐dominated stages I and II evaporation behavior, respectively. The atmospheric conditions directly affect the boundary layer during stage I. The evaporation rate is determined by the diffusion in the boundary layer, but not that in the porous media. The soil properties exert intrinsic influence on the capillary flow and determine the evaporation amount. The complex interaction between capillarity and the boundary layer leads to a heterogeneous distribution of evaporative flux with undulation (i.e., location along the soil surface) and time. Additionally, more and steeper waves indicate more influence from capillary flow, enhancing evaporation compared to a single wave system with the same wave amplitude, while steeper waves also result in a thicker boundary layer and weaken evaporation.

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“…Uncertainties in hydrological simulation brings difficulties in water resource management and hydrological risk reduction (Zhu et al, 2018;Yu et al, 2019;Shao et al, ,2018aWang et al 2018). Therefore, uncertainty and parameter estimation have become a necessary procedure in the application of hydrological models (Li, 2005).…”

Section: Glue-based Hydrological Model Uncertainty and Parameter Estimationmentioning

confidence: 99%

Improving computational efficiency of GLUE method for hydrological model uncertainty and parameter estimation using CPU-GPU hybrid high performance computer cluster

Zuo

Kan

Sun

et al. 2021

Preprint

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Abstract. The Generalized Likelihood Uncertainty Estimation (GLUE) method has been thrived for decades, huge number of applications in the field of hydrological model have proved its effectiveness in uncertainty and parameter estimation. However, for many years, the poor computational efficiency of GLUE hampers its further applications. A feasible way to solve this problem is the integration of modern CPU-GPU hybrid high performance computer cluster technology to accelerate the traditional GLUE method. In this study, we developed a CPU-GPU hybrid computer cluster-based highly parallel large-scale GLUE method to improve its computational efficiency. The Intel Xeon multi-core CPU and NVIDIA Tesla many-core GPU were adopted in this study. The source code was developed by using the MPICH2, C++ with OpenMP 2.0, and CUDA 6.5. The parallel GLUE method was tested by a widely-used hydrological model (the Xinanjiang model) to conduct performance and scalability investigation. Comparison results indicated that the parallel GLUE method outperformed the traditional serial method and have good application prospect on super computer clusters such as the ORNL Summit and Sierra of the TOP500 super computers around the world.

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The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

Abstract: The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport

Cited by 14 publications

References 62 publications

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

Experimental and Numerical Study of Evaporation From Wavy Surfaces by Coupling Free Flow and Porous Media Flow

Improving computational efficiency of GLUE method for hydrological model uncertainty and parameter estimation using CPU-GPU hybrid high performance computer cluster

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