The Experts below are selected from a list of 19752 Experts worldwide ranked by ideXlab platform

Lu Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic soil Moisture Dynamic modelling: a case study in the Loess Plateau, China
    Earth and Environmental Science Transactions of the Royal Society of Edinburgh, 2018
    Co-Authors: Cong Wang, Lu Zhang, Shuai Wang, Lei Jiao
    Abstract:

    Soil Moisture is a key factor in the ecohydrological cycle in water-limited ecosystems, and it integrates the effects of climate, soil, and vegetation. The water balance and the hydrological cycle are significantly important for vegetation restoration in water-limited regions, and these Dynamics are still poorly understood. In this study, the soil Moisture and water balance were modelled with the stochastic soil water balance model in the Loess Plateau, China. This model was verified by monitoring soil Moisture data of black locust plantations in the Yangjuangou catchment in the Loess Plateau. The influences of a rainfall regime change on soil Moisture and water balance were also explored. Three meteorological stations were selected (Yulin, Yan'an, and Luochuan) along the precipitation gradient to detect the effects of rainfall spatial variability on the soil Moisture and water balance. The results showed that soil Moisture tended to be more frequent at low levels with decreasing precipitation, and the ratio of evapotranspiration under stress in response to rainfall also changed from 74.0% in Yulin to 52.3% in Luochuan. In addition, the effects of a temporal change in rainfall regime on soil Moisture and water balance were explored at Yan'an. The soil Moisture probability density function moved to high soil Moisture in the wet period compared to the dry period of Yan'an, and the evapotranspiration under stress increased from 59.5% to 72% from the wet period to the dry period. The results of this study prove the applicability of the stochastic model in the Loess Plateau and reveal its potential for guiding the vegetation restoration in the next stage.

  • Probabilistic modelling of soil Moisture Dynamics of irrigated cropland in the North China Plain
    Hydrological Sciences Journal, 2011
    Co-Authors: Xingyao Pan, Lu Zhang, Nick Potter, Jun Xia, Yongqiang Zhang
    Abstract:

    A probabilistic soil Moisture Dynamic model is used to estimate the soil Moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil Moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic soil Moisture Dynamic model. Results showed that the model was able to capture the soil Moisture Dynamics and estimate long-term water balance reasonably well when little soil water deficit existed. The prediction of mean plant water stress during winter wheat and maize growing season quantified the suitability of the wheat-maize rotation to the soil and climate environmental conditions in North China Plain under the impact of irrigation. Under the impact of precipitation fluctuations, there is no significant bimodality of the average soil Moisture probability density function.

  • Comparison of Dynamic and static APRI-models to simulate soil water Dynamics in a vineyard over the growing season under alternate partial root-zone drip irrigation
    Agricultural Water Management, 2008
    Co-Authors: Qingyun Zhou, Shaozhong Kang, Lu Zhang
    Abstract:

    In this paper, a two-dimensional (2D) Dynamic model of root water uptake was proposed based on soil water Dynamic and root Dynamic distribution of grapevine, and a function of soil evaporation related to soil water content was defined under alternate partial root-zone drip irrigation (APDI). Then the soil water Dynamic model of APDI (Dynamic APRI-model) was developed on the basis of the 2D Dynamic model of root water uptake and soil evaporation function over the growing season. Soil water Dynamic in APDI was respectively simulated by Dynamic and static APRI-models. The simulated soil water contents by two models were compared with the measured value. Results showed that values of root-mean-square-error (RMSE) for Dynamic APRI-model were less than that of the static APRI-model either in the east side or the west side of grapevine. The average relative error between the simulated and measured value was less than 5% for Dynamic APRI-model, indicating that the Dynamic APRI-model is better than the static APRI-model in simulating the soil Moisture Dynamic throughout the growing season under the APDI.

  • Comparison of APRI and Hydrus-2D models to simulate soil water Dynamics in a vineyard under alternate partial root zone drip irrigation
    Plant and Soil, 2007
    Co-Authors: Qingyun Zhou, Shaozhong Kang, Lu Zhang
    Abstract:

    Alternate partial root zone irrigation (APRI) is a new water-saving irrigation technique. It can reduce irrigation water and transpiration without reduction in crop yield, thus increase water and nutrient use efficiency. Understanding of soil Moisture distribution and Dynamic under the alternate partial root zone drip irrigation (APDI) can help to develop the efficient irrigation schemes. In this paper, a two-dimensional (2D) root water uptake model was proposed based on soil water Dynamic and root distribution of grape vine, and a function of soil evaporation related to soil water content was defined under the APDI. Then the soil water Dynamic model of APDI (APRI-model) was developed based on the 2D root water uptake model and soil evaporation function combined with average measured soil Moisture content at 0–10 cm soil layer. Soil water Dynamic in APDI was respectively simulated by Hydrus-2D model and APRI-model. The simulated soil water contents by two models were compared with the measured value. The results showed that the values of root-mean-square-error (RMSE) range from 0.01 to 0.022 cm3/cm3 for APRI-model, and from 0.012 to 0.031 cm3/cm3 for Hydrus-2D model. The average relative error between the simulated and measured soil water content is about 10% for APRI-model, and from 11% to 29% for Hydrus-2D model, indicating that two models perform well in simulating soil Moisture Dynamic under the APDI, but the APRI-model is more suitable for modeling the soil water Dynamic in the arid region with greater soil evaporation and uneven root distribution.

Hu Jia - One of the best experts on this subject based on the ideXlab platform.

  • Research progress on stochastic soil Moisture Dynamic model
    Progress in geography, 2015
    Co-Authors: Hu Jia
    Abstract:

    As an important component of the earth surface system and the core of hydrological cycle, soil water controls the most basic terrestrial ecosystem patterns and processes, which is key for the healthy operation of the terrestrial ecosystem. Soil Moisture Dynamics is an indispensable part of the research on the interactions and feedbacks between hydrological processes and terrestrial ecosystem processes, which is the result of non-linear interactions among a series of hydrological, climatic, and ecological processes. Consequently, soil Moisture Dynamics needs to be studied by stochastic methods, which can reasonably describe the characteristics of soil Moisture Dynamics including the pulse, erratic, and random processes. In this article, we systematically review the development of stochastic modeling of soil water content based on the principle of soil water balance, and focus on the classification and application of these models. This review could supply some useful reference for quantitative studies of stochastic soil Moisture Dynamic processes and be beneficial to the research on ecohydrology in China. This review also could promote a better understanding of interactions between hydrological cycle and the terrestrial ecosystem, and ultimately contribute to the knowledge base on the sustainable management of water resources and ecosystems.

Qingyun Zhou - One of the best experts on this subject based on the ideXlab platform.

  • Comparison of Dynamic and static APRI-models to simulate soil water Dynamics in a vineyard over the growing season under alternate partial root-zone drip irrigation
    Agricultural Water Management, 2008
    Co-Authors: Qingyun Zhou, Shaozhong Kang, Lu Zhang
    Abstract:

    In this paper, a two-dimensional (2D) Dynamic model of root water uptake was proposed based on soil water Dynamic and root Dynamic distribution of grapevine, and a function of soil evaporation related to soil water content was defined under alternate partial root-zone drip irrigation (APDI). Then the soil water Dynamic model of APDI (Dynamic APRI-model) was developed on the basis of the 2D Dynamic model of root water uptake and soil evaporation function over the growing season. Soil water Dynamic in APDI was respectively simulated by Dynamic and static APRI-models. The simulated soil water contents by two models were compared with the measured value. Results showed that values of root-mean-square-error (RMSE) for Dynamic APRI-model were less than that of the static APRI-model either in the east side or the west side of grapevine. The average relative error between the simulated and measured value was less than 5% for Dynamic APRI-model, indicating that the Dynamic APRI-model is better than the static APRI-model in simulating the soil Moisture Dynamic throughout the growing season under the APDI.

  • Comparison of APRI and Hydrus-2D models to simulate soil water Dynamics in a vineyard under alternate partial root zone drip irrigation
    Plant and Soil, 2007
    Co-Authors: Qingyun Zhou, Shaozhong Kang, Lu Zhang
    Abstract:

    Alternate partial root zone irrigation (APRI) is a new water-saving irrigation technique. It can reduce irrigation water and transpiration without reduction in crop yield, thus increase water and nutrient use efficiency. Understanding of soil Moisture distribution and Dynamic under the alternate partial root zone drip irrigation (APDI) can help to develop the efficient irrigation schemes. In this paper, a two-dimensional (2D) root water uptake model was proposed based on soil water Dynamic and root distribution of grape vine, and a function of soil evaporation related to soil water content was defined under the APDI. Then the soil water Dynamic model of APDI (APRI-model) was developed based on the 2D root water uptake model and soil evaporation function combined with average measured soil Moisture content at 0–10 cm soil layer. Soil water Dynamic in APDI was respectively simulated by Hydrus-2D model and APRI-model. The simulated soil water contents by two models were compared with the measured value. The results showed that the values of root-mean-square-error (RMSE) range from 0.01 to 0.022 cm3/cm3 for APRI-model, and from 0.012 to 0.031 cm3/cm3 for Hydrus-2D model. The average relative error between the simulated and measured soil water content is about 10% for APRI-model, and from 11% to 29% for Hydrus-2D model, indicating that two models perform well in simulating soil Moisture Dynamic under the APDI, but the APRI-model is more suitable for modeling the soil water Dynamic in the arid region with greater soil evaporation and uneven root distribution.

Francesco Viola - One of the best experts on this subject based on the ideXlab platform.

  • Future Climate Forcings and Olive Yield in a Mediterranean Orchard
    Water, 2014
    Co-Authors: Francesco Viola, Leonardo Noto, Domenico Caracciolo, Dario Pumo, Goffredo La Loggia
    Abstract:

    The olive tree is one of the most characteristic rainfed trees in the Mediterranean region. Observed and forecasted climate modifications in this region, such as the CO2 concentration and temperature increase and the net radiation, rainfall and wind speed decrease, will likely alter vegetation water stress and modify productivity. In order to simulate how climatic change could alter soil Moisture Dynamic, biomass growth and fruit productivity, a water-driven crop model has been used in this study. The numerical model, previously calibrated on an olive orchard located in Sicily (Italy) with a satisfactory reproduction of historical olive yield data, has been forced with future climate scenarios generated using a stochastic weather generator and a downscaling procedure of an ensemble of climate model outputs. The stochastic downscaling is carried out using simulations of some General Circulation Models adopted in the fourth Intergovernmental Panel on Climate Change (IPCC) assessment report (4AR) for future scenarios. The outcomes state that climatic forcings driving potential evapotranspiration compensate for each other, resulting in a slight increase of this water demand flux; moreover, the increase of CO2 concentration leads to a potential assimilation increase and, consequently, to an overall productivity increase in spite of the growth of water stress due to the rainfall reduction.

  • Olive yield as a function of soil Moisture Dynamics
    Ecohydrology, 2011
    Co-Authors: Francesco Viola, Leonardo Noto, Marcella Cannarozzo, Goffredo La Loggia, Amilcare Porporato
    Abstract:

    This study introduces a water-driven crop model aiming to quantitatively link olive yield to climate and soil Moisture Dynamics using an ecohydrological approach. A mathematical model describing soil Moisture, evapotranspiration and assimilation Dynamics of olive orchards is developed here. The model is able to explicitly reproduce two different hydroclimatic phases in Mediterranean areas: the well-watered conditions in which evapotranspiration and assimilation assume their maximum values and the real conditions where the limitations induced by soil Moisture availability are taken into account. Annual olive yield is obtained by integrating the carbon assimilation during the growing season, including the effects of vegetation water stress on biomass allocation. This numerical model has been tested on an olive orchard located in Sicily (Italy) obtaining a satisfactory reproduction of historical olive yield data. This model is useful for simulating the influence of soil Moisture Dynamic on biomass growth, fruit productivity, also in a context of climatic change. Copyright © 2011 John Wiley & Sons, Ltd.

Chen Yong-le - One of the best experts on this subject based on the ideXlab platform.

  • Probabilistic modeling of soil Moisture Dynamics in a revegetated desert area
    Sciences in Cold and Arid Regions, 2013
    Co-Authors: Huang Lei, Zhang Zhi-shan, Chen Yong-le
    Abstract:

    Soil Moisture is the key link between land hydrological and ecological processes which plays an important role in the terrestrial water cycle. As extreme weather events have increased in recent years, the stochastic simulation of soil Moisture has gradually become the focus of ecohydrology research. Based on continuous monitoring of soil Moisture data from 2008 to 2011, and historical precipitation data from 1991 to 2011, combined with the Rodriguez-Iturbe soil Moisture Dynamic stochastic model, soil Moisture Dynamics and its probability density function in a revegetated desert area was simulated. Results show that annual soil Moisture Dynamic changes of the revegetated desert area during the growing season complied with rainfall distribution; soil Moisture probability presents a single-peak distribution in the plant rhizosphere layer (0-60 cm). The peak width in the 20 cm topsoil was wider than in other soils, and the distribution presented the strong fluctuations and multiple aggregates. The peak widths of 40 cm and 60 cm soil Moisture probability distribution were small, which are in accordance with simulated results of the Rodriguez-Iturbe model. This confirms that the Rodriguez-Iturbe model has good applicability and can well simulate the statistical characteristics of soil Moisture in an arid revegetated desert area.

  • Probabilistic Modelling of Soil Moisture Dynamics in a Revegetated Desert Area
    Journal of Desert Research, 2013
    Co-Authors: Chen Yong-le
    Abstract:

    Soil Moisture was the key link between land hydrological and ecological processes,which had play an important role in the terrestrial water cycling.With frequent and extreme weather events in recent years,the stochastic simulation of soil Moisture has gradually become the research focus in ecohydrology.Based on the continuous monitoring soil Moisture data from 2008 to 2011,the historical precipitation data from 1991 to 2011,and combined with the Rodriguez-Iturbe soil Moisture Dynamic stochastic model,we studied the soil Moisture Dynamics and its probability density function in a revegetated desert area.Results showed that,the annual soil Moisture Dynamics changed with the rainfall distribution,and the probability distribution showed a single peak-shaped in the plant rhizosphere layer(0-60 cm),the peak width in the topsoil mositure 20 cm was larger than the others,and the distribution also appeared a certain degree of jump.The 40 cm and 60 cm of soil Moisture probability distribution peak width was smaller,which was in accordance with the simulation results of Rodriguez-Iturbe model.Those results confirmed that stochastic model also had a good applicability in arid desert areas and could be well used in describing the statistical characteristics of soil Moisture.