A method for estimating soil moisture storage in regions under water stress and storage depletion: a case study of Hai River Basin,North China

Soil moisture is a consideration for soil conservation, agricultural production and climate modelling. This article presents a simple method for estimating soil moisture storage under water stress and storage depletion conditions. The method is driven by the common agro‐hydrologic variables of precipitation (PPT), irrigation (IRR) and evapotranspiration (ET). The proposed method is successfully tested for the 152 000 km² floodplain region of Hai River Basin using 48 consecutive months (2003–2006) of data. Soil moisture data from global land data assimilation system/Noah land surface model are validated with ground‐truth data from 102 soil moisture monitoring sites. The validated soil moisture is used in combination with in situ groundwater data to quantify total water storage change (TWSC) in the region. The estimated storage change is in turn compared with gravity recovery and climate experiment‐derived TWSC for the study area. The soil moisture and TWSC terms show favourable agreements, with discrepancies of < 10% on the average. While there is no consistent seasonal trend in soil moisture, TWSC shows a strong seasonality. It is low in spring and high in summer. This trend corresponds with the IRR–PPT season in the study area. Change in groundwater and total water storage indicates storage depletion in the basin. Storage depletion in the region is driven mainly by groundwater IRR and ET loss. Despite the low PPT and high ET, there is narrowing seasonal trend in soil moisture. This is achieved at the expense of groundwater storage. IRR pumping has induced extensive groundwater depletion in the basin. It is therefore vital to develop cultivation strategies that aim at limiting IRR pumping and ET loss. Water management practices that not only reduce waste but also ensure high productivity and ecological sustainability could also mitigate storage depletion in the region. These measures could reduce further not only the seasonal trend in soil moisture but also that in groundwater storage. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimation of mean water transit time on a steep hillslope in South Korea using soil moisture measurements and deuterium excess

A method for estimating daily mean transit time (DMTT) within a soil layer was proposed using field measurements of soil moisture. Vertical profiles of soil moisture time series were used for storage estimation. Water fluxes were evaluated through matrix and bypass flow. Variations in soil moisture and soil thickness were used to evaluate matrix flow. Exponential decay in depth of macropores was also used for bypass flow approximation. DMTT evaluation was compared to results obtained from a stable water isotope model using two years of data acquired on a steep granite hillslope in the Sulmachun watershed, South Korea. Various uncertainties in transit time evaluation such as model structure, non‐stationary assumption and data acquisition of existing approaches can be accounted for in the proposed methodology, and the flowpath contribution can be further configured in conjunction with hydrometric measurements. Probability density functions of isotope analyses were partially explained by transit time distributions that were based on soil moisture measurements. Supplementary sensitivity analyses for uncertainty configurations indicate that matrix flow is the primary process in determining transit time distribution while the impact of bypass flow is minor. The feasibility of a DMTT approach over isotope‐based methodologies highlights not only the strength of this proposed method, both in cost and time, but also its further application potential for existing soil moisture measurements. Copyright © 2013 John Wiley & Sons, Ltd.     

Improvement of a simplified process‐based model for estimating transpiration under water‐limited conditions

Plant transpiration depends on environmental conditions, and soil water availability is its primary control under water deficit conditions. In this study, we improve a simplified process‐based model (hereafter “BTA”) by including soil water potential (ψ_soil) to explicitly represent the dependence of plant transpiration on root‐zone moisture conditions. The improved model is denoted as the BTA‐ψ model. We assessed the performance of the BTA and BTA‐ψ models in a subtropical monsoon climate and a Mediterranean climate with different levels of water stress. The BTA model performed reasonably in estimating daily and hourly transpiration under sufficient water conditions, but it failed during dry periods. Overall, the BTA‐ψ model provided a significant improvement for estimating transpiration under a wide range of soil moisture conditions. Although both models could estimate transpiration (sap flow) at night, BTA‐ψ was superior to BTA in this regard. Species differences in the calibrated parameters of both models were consistent with leaf‐level photosynthetic measurements on each species, as expected given the physiological basis of these parameters. With a simplified representation of physiological regulation and reasonable performance across a range of soil moisture conditions, the BTA‐ψ model provides a useful alternative to purely empirical models for modelling transpiration.     

A tracer‐based simulation approach to quantify seasonal dynamics of surface‐groundwater interactions in the Pantanal wetland

The Pantanal wetland is one of the least explored regions of South America. It is characterized by an outstanding flora and fauna adapted to a seasonal flood pulse controlled by a dry and a wet season within each year. The resulting inundation covers in average an area of approximately 150 000 km² and is seen as the most important driver for ecological integrity. Evaporation from the large floodplain is supposed to influence the climate of the whole continent. The regional groundwater is connected to the surface water and plays an important role for the characteristic flooding regime by regulating the wetland's water table. The water balance assessment of the wetland and the internal water exchange between surface and groundwater is therefore of high relevance for the conservation of the Pantanal biodiversity. Despite of its importance, water balance studies including groundwater–surface water interactions based on field data are rarely undertaken. This is mainly due to the remoteness and difficulty in accessing this area, which results in lack of data. In our study, we developed a new tracer‐based model to simulate the spatio–temporal surface and subsurface fluxes for a range of water bodies. The model was able to simulate these fluxes considering a dynamic simulation of inflow and outflow using a newly collected 2‐year dataset of water levels, stable water isotopes and chloride collected from several water bodies in the northern Pantanal region. Quantitative differences between water bodies according to their location in the floodplain were determined by the flooding regime and connectivity as well as site‐specific characteristics, such as hydraulic conductivity and water depth. Our model simulated water balance fluxes with a Nash–Sutcliffe efficiency of 0.61, whereas it simulated stable water isotopic compositions better than chloride. We present the first study based on field data for the Pantanal, which is able to quantify water balances fluxes. Because their representation in global climate and land cover products is insufficient, our simulation results are valuable for validating large‐scale models. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluation of the hydrology of the IBIS land surface model in a semi‐arid catchment

This paper evaluates the Integrated BIosphere Simulator (IBIS) land surface model using daily soil moisture data over a 3‐year period (2005–2007) at a semi‐arid site in southeastern Australia, the Stanley catchment, using the Monte Carlo generalized likelihood uncertainty estimation (GLUE) approach. The model was satisfactorily calibrated for both the surface 30 cm and full profile 90 cm. However, full‐profile calibration was not as good as that for the surface, which results from some deficiencies in the evapotranspiration component in IBIS. Relatively small differences in simulated soil moisture were associated with large discrepancies in the predictions of surface runoff, drainage and evapotranspiration. We conclude that while land surface schemes may be effective at simulating heat fluxes, they may be ineffective for prediction of hydrology unless the soil moisture is accurately estimated. Sensitivity analyses indicated that the soil moisture simulations were most sensitive to soil parameters, and the wilting point was the most identifiable parameter. Significant interactions existed between three soils parameters: porosity, saturated hydraulic conductivity and Campbell ‘b’ exponent, so they could not be identified independent of each other. There were no significant differences in parameter sensitivity and interaction for different hydroclimatic years. Even though the data record contained a very dry year and another year with a very large rainfall event, this indicated that the soil model could be calibrated without the data needing to explore the extreme range of dry and wet conditions. IBIS was much less sensitive to vegetation parameters. The leaf area index (LAI) could affect the mean of daily soil moisture time series when LAI < 1, while the variance of the soil moisture time series was sensitive to LAI > 1. IBIS was insensitive to the Jackson rooting parameter, suggesting that the effect of the rooting depth distribution on predictions of hydrology was insignificant. Copyright © 2014 John Wiley & Sons, Ltd.     

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture,groundwater, and digital elevation data

Inadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.     

Simulation of groundwater dynamics in the North China Plain by coupled hydrology and agricultural models

We simulated the effects of irrigation on groundwater flow dynamics in the North China Plain by coupling the NIES Integrated Catchment‐based Ecohydrology (NICE) model with DSSAT‐wheat and DSSAT‐maize, two agricultural models. This combined model (NICE‐AGR) was applied to the Hai River catchment and the lower reach of the Yellow River (530 km wide by 840 km long) at a resolution of 5 km. It reproduced excellently the soil moisture, evapotranspiration and crop production of summer maize and winter wheat, correctly estimating crop water use. So, the spatial distribution of crop water use was reasonably estimated at daily steps in the simulation area. In particular, NICE‐AGR reproduced groundwater levels better than the use of statistical water use data. This indicates that NICE‐AGR does not need detailed statistical data on water use, making it very powerful for evaluating and estimating the water dynamics of catchments with little statistical data on seasonal water use. Furthermore, the simulation reproduced the spatial distribution of groundwater level in 1987 and 1988 in the Hebei Plain, showing a major reduction of groundwater level due mainly to overpumping for irrigation. Copyright © 2006 John Wiley & Sons, Ltd.     

Spatial prediction of temporal soil moisture dynamics using HYDRUS‐1D

This article investigates the soil moisture dynamics within two catchments (Stanley and Krui) in the Goulburn River in NSW during a 3‐year period (2005–2007) using the HYDRUS‐1D soil water model. Sensitivity analyses indicated that soil type, and leaf area index were the key parameters affecting model performance. The model was satisfactorily calibrated on the Stanley microcatchment sites with a single point rainfall record from this microcatchment for both surface 30 cm and full‐profile soil moisture measurements. Good correlations were obtained between observed and simulated soil water storage when calibrations for one site were applied to the other sites. We extended the predictions of soil moisture to a larger spatial scale using the calibrated soil and vegetation parameters to the sites in the Krui catchment where soil moisture measurement sites were up to 30 km distant from Stanley. Similarly good results show that it is possible to use a calibrated soil moisture model with measurements at a single site to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000 km² given similar soils and vegetation and local rainfall data. Site predictions were effectively improved by our simple data assimilation method using only a few sample data collected from the site. This article demonstrates the potential usefulness of continuous time, point‐scale soil moisture data (typical of that measured by permanently installed TDR probes) and simulations for predicting the soil wetness status over a catchment of significant size (up to 1000 km²). Copyright © 2012 John Wiley & Sons, Ltd.     

Multi‐variable and multi‐site calibration and validation of SWAT in a large mountainous catchment with high spatial variability

Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi‐variable and multi‐site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11‐year historical flow record (1990–2000); 1990–94 was used for calibration and 1995–2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash–Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub‐basins, and subcatchments). The use of an integrated multi‐variable and multi‐site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

A soil‐water‐balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain

Rapidly depleting unconfined aquifers are the primary source of water for irrigation on the North China Plain. Yet, despite its critical importance, groundwater recharge to the Plain remains an enigma. We introduce a one‐dimensional soil‐water‐balance model to estimate precipitation‐ and irrigation‐generated areal recharge from commonly available crop and soil characteristics and climate data. To limit input data needs and to simplify calculations, the model assumes that water flows vertically downward under a unit gradient; infiltration and evapotranspiration are separate, sequential processes; evapotranspiration is allocated to evaporation and transpiration as a function of leaf‐area index and is limited by soil‐moisture content; and evaporation and transpiration are distributed through the soil profile as exponential functions of soil and root depth, respectively. For calibration, model‐calculated water contents of 11 soil‐depth intervals from 0 to 200 cm were compared with measured water contents of loam soil at four sites in Luancheng County, Hebei Province, over 3 years (1998–2001). Each 50‐m² site was identically cropped with winter wheat and summer maize, but received a different irrigation treatment. Average root mean‐squared error between measured and model‐calculated water content of the top 180 cm was 4·2 cm, or 9·3% of average total water content. In addition, model‐calculated evapotranspiration compared well with that measured by a large‐scale lysimeter. To test the model, 12 additional sites were simulated successfully. Model results demonstrate that drainage from the soil profile is not a constant fraction of precipitation and irrigation inputs, but rather the fraction increases as the inputs increase. Because this drainage recharges the underlying aquifer, improving irrigation efficiency by reducing seepage will not reverse water‐table declines. Copyright © 2003 John Wiley & Sons, Ltd.     

A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa

The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi‐temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR‐E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time‐lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21‐day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of soil moisture heterogeneity length scale and gradients on daytime coupled land‐cloudy boundary layer interactions

Using a coupled large‐eddy simulation–land surface model framework, the impact of two‐dimensional soil moisture heterogeneity on the cloudy boundary layer under varied free‐atmosphere stabilities is investigated. Specifically, the impacts of soil moisture heterogeneity length scale and heterogeneity in terms of soil moisture gradients on micrometeorological states, surface fluxes, boundary layer characteristics, and cloud development are examined. The results show that mesoscale circulations due to surface heterogeneity in soil moisture play an important role in transferring water vapour within the boundary layer and in regulating cloud distribution at the entrainment zone, which, in turn, provides feedbacks on boundary layer/surface energy budgets. The initial domain‐averaged soil moisture is identical for all homogenous and heterogeneous cases; however, the soil moisture heterogeneity in gradient and length scale between dry and wet regions has a significant impact on the estimates of near‐surface micrometeorological properties and surface fluxes, which further affect the boundary layer states and characteristics. Both liquid water potential temperature and liquid water mixing ratio increase with an increasing soil moisture gradient, whereas the amount of specific humidity decreases. Heterogeneity length scale and free atmosphere stability also amplify these impacts on the boundary layer structure and cloud formation. In a low atmospheric stability condition that potentially allows for a deeper boundary layer and a higher entrainment rate, cloud base height and cloud thickness significantly increase as the soil moisture gradient and length scale increase. Analysis to differentiate the influences of surface heterogeneity type (i.e. length scale vs gradient) shows that in general soil moisture gradient provides a larger impact than heterogeneity length scale, although the heterogeneity length scale is large enough to initiate circulation features responsible for differences in the coupled system between homogeneous and heterogeneous soil moisture cases. Copyright © 2012 John Wiley & Sons, Ltd.     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

Spatio‐temporal variability of water and energy fluxes – a case study for a mesoscale catchment in pre‐alpine environment

Water and energy fluxes at and between the land surface, the subsurface and the atmosphere are inextricably linked over all spatio‐temporal scales. Our research focuses on the joint analysis of both water and energy fluxes in a pre‐alpine catchment (55 km²) in southern Germany, which is part of the Terrestrial Environmental Observatories (TERENO). We use a novel three‐dimensional, physically based and distributed modelling approach to reproduce both observed streamflow as an integral measure for water fluxes and heat flux and soil temperature measurements at an observation location over a period of 2 years. While heat fluxes are often used for comparison of the simulations of one‐dimensional land surface models, they are rarely used for additional validation of physically based and distributed hydrological modelling approaches. The spatio‐temporal variability of the water and energy balance components and their partitioning for dominant land use types of the study region are investigated. The model shows good performance for simulating daily streamflow (Nash–Sutcliffe efficiency > 0.75). Albeit only streamflow measurements are used for calibration, the simulations of hourly heat fluxes and soil temperatures at the observation site also show a good performance, particularly during summer. A limitation of the model is the simulation of temperature‐driven heat fluxes during winter, when the soil is covered by snow. An analysis of the simulated spatial fields reveals heat flux patterns that reflect the distribution of the land use and soil types of the catchment. The water and energy partitioning is characterized by a strong seasonal cycle and shows clear differences between the selected land use types. Copyright © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.     

Multi‐scale assimilation of root zone soil water predictions

When hydrology model parameters are determined, a traditional data assimilation method (such as Kalman filter) and a hydrology model can estimate the root zone soil water with uncertain state variables (such as initial soil water content). The simulated result can be quite good. However, when a key soil hydraulic property, such as the saturated hydraulic conductivity, is overestimated or underestimated, the traditional soil water assimilation process will produce a persistent bias in its predictions. In this paper, we present and demonstrate a new multi‐scale assimilation method by combining the direct insertion assimilation method, particle swarm optimisation (PSO) algorithm and Richards equation. We study the possibility of estimating root zone soil water with a multi‐scale assimilation method by using observed in situ data from the Wudaogou experiment station, Huaihe River Basin, China. The results indicate there is a persistent bias between simulated and observed values when the direct insertion assimilation surface soil water content is used to estimate root zone soil water contents. Using a multi‐scale assimilation method (PSO algorithm and direct insertion assimilation) and an assumed bottom boundary condition, the results show some obvious improvement, but the root mean square error is still relatively large. When the bottom boundary condition is similar to the actual situation, the multi‐scale assimilation method can well represent the root zone soil water content. The results indicate that the method is useful in estimating root zone soil water when available soil water data are limited to the surface layer and the initial soil water content even when the soil hydraulic conductivities are uncertain. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessment of evaporation and water fluxes in a column of dry saline soil subject to different water table levels

Dry saline soils are common in the arid and hyper‐arid basins located in the Chilean Altiplano, where evaporation from shallow groundwater is typically the major component of the water balance. Thus, a good understanding of evaporation processes is necessary for improving water resource planning and management in these regions. In this study, we conducted laboratory experiments with a natural saline soil column to estimate evaporation rates and assess the liquid and water vapor fluxes under different water table levels. Water content, electrical conductivity and temperature at different depths were utilized to assess the liquid and water vapor fluxes in the soil column. We observed movement of water that dissolves salts from the soil and transports them to areas in the column where they accumulate. Isothermal liquid flux was predominant, while thermal and isothermal liquid and thermal water vapor fluxes were negligible, except for deep water table levels where isothermal and thermal water vapor fluxes had similar magnitude but opposite directions. Differences observed in total fluxes for all water table levels were due to different upward and downward fluxes, which depend on changes in water content and temperature within the soil profile. Both the vapor flux magnitude and direction were found to be very sensitive to the choice of empirical parameters used in flux quantification, such as tortuosity and the enhancement factor for local temperature gradients in the air phase within the column. Copyright © 2013 John Wiley & Sons, Ltd.     

Improving soil moisture accounting and streamflow prediction in SWAT by incorporating a modified time‐dependent Curve Number method

The objective of this study is to incorporate a time‐dependent Soil Moisture Accounting (SMA) based Curve Number method (SMA_CN) in Soil and Water Assessment Tool (SWAT) and compare its performance with the existing CN method in SWAT by simulating the hydrology of two agricultural watersheds in Indiana, USA. Results show that fusion of the SMA_CN method causes decrease in runoff volume and increase in profile soil moisture content, associated with larger groundwater contribution to the streamflow. In addition, the higher amount of moisture in the soil profile slightly elevates the actual evapotranspiration. The SMA‐based SWAT configuration consistently produces improved goodness‐of‐fit scores and less uncertain outputs with respect to streamflow during both calibration and validation. The SMA_CN method exhibits a better match with the observed data for all flow regimes, thereby addressing issues related to peak and low flow predictions by SWAT in many past studies. Comparison of the calibrated model outputs with field‐scale soil moisture observations reveals that the SMA overhauling enables SWAT to represent soil moisture condition more accurately, with better response to the incident rainfall dynamics. While the results from the modification of the CN method in SWAT are promising, more studies including watersheds with various physical and climatic settings are needed to validate the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.     

Groundwater Recharge at Five Representative Sites in the Hebei Plain,China

Accurate estimates of groundwater recharge are essential for effective management of groundwater, especially when supplies are limited such as in many arid and semiarid areas. In the Hebei Plain, China, water shortage is increasingly restricting socioeconomic development, especially for agriculture, which heavily relies on groundwater. Human activities have greatly changed groundwater recharge there during the past several decades. To obtain better estimates of recharge in the plain, five representative sites were selected to investigate the effects of irrigation and water table depth on groundwater recharge. At each site, a one‐dimensional unsaturated flow model (Hydrus‐1D) was calibrated using field data of climate, soil moisture, and groundwater levels. A sensitivity analysis of evapotranspirative fluxes and various soil hydraulic parameters confirmed that fine‐textured surface soils generally generate less recharge. Model calculations showed that recharge on average is about 175 mm/year in the piedmont plain to the west, and 133 mm/year in both the central alluvial and lacustrine plains and the coastal plain to the east. Temporal and spatial variations in the recharge processes were significant in response to rainfall and irrigation. Peak time‐lags between infiltration (rainfall plus irrigation) and recharge were 18 to 35 days in the piedmont plain and 3 to 5 days in the central alluvial and lacustrine plains, but only 1 or 2 days in the coastal plain. This implies that different time‐lags corresponding to different water table depths must be considered when estimating or modeling groundwater recharge.