scholarly journals A Soil Moisture‐Dependent Model to Simulate Water Table Depth and Proportions of Surface and Subsurface Runoff and Its Validation at the Basin Scale

2021 ◽  
Vol 126 (4) ◽  
Author(s):  
Meizhao Lv ◽  
Zong‐Liang Yang ◽  
Zhongfeng Xu ◽  
Li Dan ◽  
Meixia Lv ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Water Table Depth ◽  
Basin Scale ◽  
Dependent Model ◽  
Subsurface Runoff

scholarly journals Development of a Coupled Land Surface and Groundwater Model

2005 ◽  
Vol 6 (3) ◽  
pp. 233-247 ◽  
Author(s):  
Reed M. Maxwell ◽  
Norman L. Miller
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Lower Boundary ◽  
Coupled Model ◽  
Water Table Depth ◽  
Frozen Soil ◽  
Coupled Models ◽  
Common Land Model

Abstract Traditional land surface models (LSMs) used for numerical weather simulation, climate projection, and as inputs to water management decision support systems, do not treat the LSM lower boundary in a fully process-based fashion. LSMs have evolved from a leaky-bucket approximation to more sophisticated land surface water and energy budget models that typically have a specified bottom layer flux to depict the lowest model layer exchange with deeper aquifers. The LSM lower boundary is often assumed zero flux or the soil moisture content is set to a constant value; an approach that while mass conservative, ignores processes that can alter surface fluxes, runoff, and water quantity and quality. Conversely, groundwater models (GWMs) for saturated and unsaturated water flow, while addressing important features such as subsurface heterogeneity and three-dimensional flow, often have overly simplified upper boundary conditions that ignore soil heating, runoff, snow, and root-zone uptake. In the present study, a state-of-the-art LSM (Common Land Model) and a variably saturated GWM (ParFlow) have been coupled as a single-column model. A set of simulations based on synthetic data and data from the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS), version 2(d), 18-yr dataset from Valdai, Russia, demonstrate the temporal dynamics of this coupled modeling system. The soil moisture and water table depth simulated by the coupled model agree well with the Valdai observations. Differences in prediction between the coupled and uncoupled models demonstrate the effect of a dynamic water table on simulated watershed flow. Comparison of the coupled model predictions with observations indicates certain cold processes such as frozen soil and freeze/thaw processes have an important impact on predicted water table depth. Comparisons of soil moisture, latent heat, sensible heat, temperature, runoff, and predicted groundwater depth between the uncoupled and coupled models demonstrate the need for improved groundwater representation in land surface schemes.

scholarly journals Response of Hybrid Bermudagrass and Manilagrass to Soil Moisture Using Water-table Depth Gradient Tanks

HortScience ◽  
2021 ◽  
pp. 1-7
Author(s):  
Gerald Henry ◽  
Rebecca Grubbs ◽  
Chase Straw ◽  
Kevin Tucker ◽  
Jared Hoyle
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Field Capacity ◽  
Water Table Depth ◽  
Habitat Specialization ◽  
Depth Gradient ◽  
Turfgrass Quality

Previous research involving turfgrass response to soil moisture used methodology that may compromise root morphology or fail to control outside environmental factors. Water-table depth gradient tanks were employed in the greenhouse to identify habitat specialization of hybrid bermudagrass [Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt-Davy] and manilagrass [Zoysia matrella (L.) Merr.] maintained at 2.5 and 5.1 cm. Turfgrass quality (TQ), normalized difference vegetation index (NDVI), canopy temperature (CT), and root biomass (RB) were used as metrics for plants grown in monoculture in sandy clay loam soil. Mowing height did not affect growth of turfgrass species in response to soil moisture. Turfgrass quality, NDVI, and RB were greatest, whereas CT was lowest at wetter levels [27- to 58-cm depth to the water-table (DWT)] of each tank where plants were growing at or above field capacity. However, bermudagrass RB was greatest at 27-cm DWT, whereas manilagrass RB at 27-cm DWT was lower than RB at 42.5- to 73.5-cm DWT in 2013 and lower than all other levels in 2014. Both species responded similarly to droughty levels (120- to 151-cm DWT) of the tanks. Turfgrass quality, NDVI, and RB were lowest, whereas CT was highest at higher droughty levels. Bermudagrass may be more competitive than manilagrass when soil moisture is high whereas both species are less competitive when soil moisture is low.

scholarly journals Assimilation of SMOS soil moisture into a distributed hydrological model and impacts on the water cycle variables over the Ouémé catchment in Benin

2016 ◽  
Vol 20 (7) ◽  
pp. 2827-2840 ◽  
Author(s):  
Delphine J. Leroux ◽  
Thierry Pellarin ◽  
Théo Vischel ◽  
Jean-Martial Cohard ◽  
Tania Gascon ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Water Table ◽  
Hydrological Model ◽  
Water Cycle ◽  
Tropical Rainfall Measuring Mission ◽  
Water Table Depth ◽  
Distributed Hydrological Model ◽  
Model Soil ◽  
Precipitation Estimation

Abstract. Precipitation forcing is usually the main source of uncertainty in hydrology. It is of crucial importance to use accurate forcing in order to obtain a good distribution of the water throughout the basin. For real-time applications, satellite observations allow quasi-real-time precipitation monitoring like the products PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, TRMM (Tropical Rainfall Measuring Mission) or CMORPH (CPC (Climate Prediction Center) MORPHing). However, especially in West Africa, these precipitation satellite products are highly inaccurate and the water amount can vary by a factor of 2. A post-adjusted version of these products exists but is available with a 2 to 3 month delay, which is not suitable for real-time hydrologic applications. The purpose of this work is to show the possible synergy between quasi-real-time satellite precipitation and soil moisture by assimilating the latter into a hydrological model. Soil Moisture Ocean Salinity (SMOS) soil moisture is assimilated into the Distributed Hydrology Soil Vegetation Model (DHSVM) model. By adjusting the soil water content, water table depth and streamflow simulations are much improved compared to real-time precipitation without assimilation: soil moisture bias is decreased even at deeper soil layers, correlation of the water table depth is improved from 0.09–0.70 to 0.82–0.87, and the Nash coefficients of the streamflow go from negative to positive. Overall, the statistics tend to get closer to those from the reanalyzed precipitation. Soil moisture assimilation represents a fair alternative to reanalyzed rainfall products, which can take several months before being available, which could lead to a better management of available water resources and extreme events.

scholarly journals A Comparison of Three Trapezoid Models Using Optical and Thermal Satellite Imagery for Water Table Depth Monitoring in Estonian Bogs

2020 ◽  
Vol 12 (12) ◽  
pp. 1980 ◽  
Author(s):  
Iuliia Burdun ◽  
Michel Bechtold ◽  
Valentina Sagris ◽  
Viacheslav Komisarenko ◽  
Gabrielle De Lannoy ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Satellite Imagery ◽  
Landsat Imagery ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Water Table Depth ◽  
P Value

This study explored the potential of optical and thermal satellite imagery to monitor temporal and spatial changes in the position of the water table depth (WTD) in the peat layer of northern bogs. We evaluated three different trapezoid models that are proposed in the literature for soil moisture monitoring in regions with mineral soils. Due to the tight capillary connection between water table and surface soil moisture, we hypothesized that the soil moisture indices retrieved from these models would be correlated with WTD measured in situ. Two trapezoid models were based on optical and thermal imagery, also known as Thermal-Optical TRApezoid Models (TOTRAM), and one was based on optical imagery alone, also known as the OPtical TRApezoid Model (OPTRAM). The models were applied to Landsat imagery from 2008 to 2019 and the derived soil moisture indices were compared with in-situ WTD from eight locations in two Estonian bogs. Our results show that only the OPTRAM index was significantly (p-value < 0.05) correlated in time with WTD (average Pearson correlation coefficient of 0.41 and 0.37, for original and anomaly time series, respectively), while the two tested TOTRAM indices were not. The highest temporal correlation coefficients (up to 0.8) were observed for OPTRAM over treeless parts of the bogs. An assessment of the spatial correlation between soil moisture indices and WTD indicated that all three models did not capture the spatial variation in water table depth. Instead, the spatial patterns of the indices were primarily attributable to vegetation patterns.

scholarly journals Quantifying the impact of groundwater depth on evapotranspiration in a semi-arid grassland region

2011 ◽  
Vol 15 (3) ◽  
pp. 787-806 ◽  
Author(s):  
M. E. Soylu ◽  
E. Istanbulluoglu ◽  
J. D. Lenters ◽  
T. Wang
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Interactions ◽  
Water Table Depth ◽  
Richards Equation ◽  
Hydraulic Parameter ◽  
Soil Hydraulic ◽  
Semi Arid

Abstract. Interactions between shallow groundwater and land surface processes play an important role in the ecohydrology of riparian zones. Some recent land surface models (LSMs) incorporate groundwater-land surface interactions using parameterizations at varying levels of detail. In this paper, we examine the sensitivity of land surface evapotranspiration (ET) to water table depth, soil texture, and two commonly used soil hydraulic parameter datasets using four models with varying levels of complexity. The selected models are Hydrus-1D, which solves the pressure-based Richards equation, the Integrated Biosphere Simulator (IBIS), which simulates interactions among multiple soil layers using a (water-content) variant of the Richards equation, and two forms of a steady-state capillary flux model coupled with a single-bucket soil moisture model. These models are first evaluated using field observations of climate, soil moisture, and groundwater levels at a semi-arid site in south-central Nebraska, USA. All four models are found to compare reasonably well with observations, particularly when the effects of groundwater are included. We then examine the sensitivity of modelled ET to water table depth for various model formulations, node spacings, and soil textures (using soil hydraulic parameter values from two different sources, namely Rawls and Clapp-Hornberger). The results indicate a strong influence of soil texture and water table depth on groundwater contributions to ET. Furthermore, differences in texture-specific, class-averaged soil parameters obtained from the two literature sources lead to large differences in the simulated depth and thickness of the "critical zone" (i.e., the zone within which variations in water table depth strongly impact surface ET). Depending on the depth-to-groundwater, this can also lead to large discrepancies in simulated ET (in some cases by more than a factor of two). When the Clapp-Hornberger soil parameter dataset is used, the critical zone becomes significantly deeper, and surface ET rates become much higher, resulting in a stronger influence of deep groundwater on the land surface energy and water balance. In general, we find that the simulated sensitivity of ET to the choice of soil hydraulic parameter dataset is greater than the sensitivity to soil texture defined within each dataset, or even to the choice of model formulation. Thus, our findings underscore the need for future modelling and field-based studies to improve the predictability of groundwater-land surface interactions in numerical models, particularly as it relates to the parameterization of soil hydraulic properties.

scholarly journals Real-time forecasting of water table depth and soil moisture profiles

2006 ◽  
Vol 29 (5) ◽  
pp. 692-706 ◽  
Author(s):  
Ate Visser ◽  
Roelof Stuurman ◽  
Marc F.P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Water Table ◽  
Water Table Depth ◽  
Moisture Profiles

scholarly journals Environmental modifiers of the relationship between water table depth and Ellenberg’s indicator of soil moisture

2021 ◽  
Vol 132 ◽  
pp. 108320
Author(s):  
Ciara Dwyer ◽  
Jonathan Millett ◽  
Robin J. Pakeman ◽  
Laurence Jones
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Water Table Depth ◽  
The Relationship

IMPACTS OF WATER TABLE AND SOIL AMELIORANT ON SOIL MOISTURE, CO2 EMISSION, AND OIL PALM YIELD ON PEAT SOIL

2017 ◽  
Vol 25 (3) ◽  
pp. 147-160
Author(s):  
Winarna Winarna ◽  
Muhammad Arif Yusuf ◽  
Suroso Rahutomo ◽  
Edy Sigit Sutarta
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Table ◽  
Oil Palm ◽  
Co2 Emission ◽  
Peat Soil ◽  
Water Table Depth ◽  
Water Table Management ◽  
Soil Ameliorant ◽  
Sludge Application

A field study on peat soil to investigate impacts of soil water table depth and soil ameliorant (steel sludge) had been carried out on mature oil palm. Three treatments of soil water table management and four rates of steel sludge application were applied in this study. Treatments of soil water table management were WLM1, WLM-2, and WLM-3, where soil water table depth was maintained at 35-50 cm, 60-75 cm, and >75 cm below the soil surface, respectively. Treatments of steel sludge were application of this soil ameliorant at the rate of 0; 3.15; 6.51; 9.86 kg tree-1. The study was arranged as split plot randomized block design by assigning soil water table management as main plot and rate of steel sludge as sub plot. Soil Data observed were actual soil water content, peat soil properties, CO2 emission, vegetative growth, and palm yield. The results showed that maintaining soil water table depth at < 75 cm could maintain actual soil moisture up to top parts of peat soil. On the other hand, deeper soil water table (>75 cm, WLM-3) caused significant effects on decreasing of soil moisture in the 0-10 cm layer of peat soil. CO2 emission was 37, 40, dan 45 ton ha-1 year-1 under WLM-1, WLM-2, and WLM-3, respectively. The drop of soil water table to >75 cm (WLM-3) significantly increased CO2 emission to about 11-18% higher than that on WLM-1 and WLM-2. Steel sludge application did not significantly decrease CO2 emission. The highest FFB yield was observed under WLM-1, then followed by WLM-2 and WLM-3. FFB yield was significantly higher when soil water depth was maintained at 35-75 cm than that at > 75 cm, it was 7-10% and 36-60% higher in 2014 and 2015, respectively. There were no significant effects of steel sludge application on FFB yield, but there was improvement on average bunch weight.

scholarly journals Quantitative Estimation of Soil-Ground Water Storage Utilization during the Crop Growing Season in Arid Regions with Shallow Water Table Depth

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3351
Author(s):  
Tianxing Zhao ◽  
Yan Zhu ◽  
Jingwei Wu ◽  
Ming Ye ◽  
Wei Mao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Ground Water ◽  
Shallow Water ◽  
Water Table ◽  
Soil Moisture Content ◽  
Water Storage ◽  
Growing Season ◽  
Water Table Depth ◽  
Arid Areas ◽  
Shallow Water Table

Water storage in unsaturated and saturated zones during the crop non-growing season is one of the important supplementary water resources to meet crop water requirements in arid areas with shallow water table depth. It is necessary to analyze utilization of the soil-ground water storage during the crop growing season and its attribution to irrigation during the non-growing season. To facilitate the analysis, a new method based on measurements of soil moisture content and water table depth is developed. The measurements used in this study include (1) 15-year data of soil moisture content within a depth of 1 m from the land surface and water table depth measured in Jiefangzha, including its four subareas and (2) 4-year data of the same kind in Yonglian, located in arid northern China. The soil-ground water storage utilization is calculated as the difference of water storage between the beginning and end of the crop growing season in the whole computational soil profile. The results of average soil-ground water storage utilization in Jiefangzha and its four subareas and Yonglian are 121 mm, 126 mm, 113 mm, 124 mm, 185 mm and 117 mm, and the corresponding average utilization efficiencies in the non-growing season are 32.2%, 32.5%, 31.5%, 31.6%, 57.3% and 47.6%, respectively. Further, the water table fluctuation method was used to estimate the variation in water storage. The coefficients of soil-ground water storage utilization, soil-ground water storage utilization below 1 m soil depth and ground water utilization are defined, and their average values are 0.271, 0.111 and 0.026 in Jiefangzha, respectively. Then, the contribution of soil-ground water storage utilization to actual evapotranspiration is evaluated, which are over 23.5% in Jiefangzha and Yonglian. These results indicate that the soil-ground water storage plays an important role in the ecological environment in arid areas with shallow water table depth.

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