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  • Publication
    Accès libre
    Salix psammophila afforestations can cause a decline of the water table, prevent groundwater recharge and reduce effective infiltration
    (2021-8)
    Zhang, Zaiyong
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    Wang, Wenke
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    Gong, Chengcheng
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    Zhao, Ming
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    Hendricks Franssen, Harrie-Jan
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    Afforestation can reduce desertification and soil erosion. However, the hydrologic implications of afforestation are not well investigated, especially in arid and semi-arid regions. China has the largest area of afforestation in the world, with one-third of the world's total plantation forests. How the shrubs affect evapotranspiration, soil moisture dynamics, and groundwater recharge remains unclear. We designed two pairs of lysimeters, one being 1.2 m deep and the other one 4.2 m deep. Each pair consists of one lysimeter with bare soil, while on the other one a shrub is planted. The different water table depths were implemented to understand how depth to groundwater affects soil moisture and water table dynamics under different hydrological conditions. Soil moisture, water table depth, sap flow, and rainfall were measured concurrently. Our study confirms that for the current meteorological conditions in the Ordos plateau recharge is reduced or even prohibited through the large-scale plantation Salix psammophila. Shrubs also raise the threshold of precipitation required to increase soil moisture of the surface ground. For the conditions we analyzed, a minimum of 6 mm of precipitation was required for infiltration processes to commence. In addition to the hydrological analysis, the density of root distribution is assessed outside of the lysimeters for different water table depths. The results suggest that the root-density distribution is strongly affected by water table depth. Our results have important implications for the determination of the optimal shrub-density in future plantations, as well as for the conceptualization of plant roots in upcoming numerical models.
  • Publication
    Accès libre
    Spatial and temporal dynamics of deep percolation, lag time and recharge in an irrigated semi-arid region
    (2018-5)
    Nazarieh, Farzaneh
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    Ansari, H.
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    Ziaei, A. N.
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    Izady, A.
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    Davari, K.
    ;
    The time required for deep percolating water to reach the water table can be considerable in areas with a thick vadose zone. Sustainable groundwater management, therefore, has to consider the spatial and temporal dynamics of groundwater recharge. The key parameters that control the lag time have been widely examined in soil physics using small-scale lysimeters and modeling studies. However, only a small number of studies have analyzed how deep-percolation rates affect groundwater recharge dynamics over large spatial scales. This study examined how the parameters influencing lag time affect groundwater recharge in a semi-arid catchment under irrigation (in northeastern Iran) using a numerical modeling approach. Flow simulations were performed by the MODFLOW-NWT code with the Vadose-Zone Flow (UZF) Package. Calibration of the groundwater model was based on data from 48 observation wells. Flow simulations showed that lag times vary from 1 to more than 100 months. A sensitivity analysis demonstrated that during drought conditions, the lag time was highly sensitive to the rate of deep percolation. The study illustrated two critical points: (1) the importance of providing estimates of the lag time as a basis for sustainable groundwater management, and (2) lag time not only depends on factors such as soil hydraulic conductivity or vadose zone depth but also depends on the deeppercolation rates and the antecedent soil-moisture condition. Therefore, estimates of the lag time have to be associated with specific percolation rates, in addition to depth to groundwater and soil properties.
  • Publication
    Accès libre
    The influence of model structure on groundwater recharge rates in climate-change impact studies
    Numerous modeling approaches are available to provide insight into the relationship between climate change and groundwater recharge. However, several aspects of how hydrological model choice and structure affect recharge predictions have not been fully explored, unlike the well-established variability of climate model chains—combination of global climate models (GCM) and regional climate models (RCM). Furthermore, the influence on predictions related to subsoil parameterization and the variability of observation data employed during calibration remain unclear. This paper compares and quantifies these different sources of uncertainty in a systematic way. The described numerical experiment is based on a heterogeneous two-dimensional reference model. Four simpler models were calibrated against the output of the reference model, and recharge predictions of both reference and simpler models were compared to evaluate the effect of model structure on climate-change impact studies. The results highlight that model simplification leads to different recharge rates under climate change, especially under extreme conditions, although the different models performed similarly under historical climate conditions. Extreme weather conditions lead to model bias in the predictions and therefore must be considered. Consequently, the chosen calibration strategy is important and, if possible, the calibration data set should include climatic extremes in order to minimise model bias introduced by the calibration. The results strongly suggest that ensembles of climate projections should be coupled with ensembles of hydrogeological models to produce credible predictions of future recharge and with the associated uncertainties.