Soil Water Components Research Articles

The transmission of isotopic signals from precipitation to groundwater and its controls: An experimental study with soil cylinders of various soil textures and burial depths in a monsoon region

The use of stable isotopic composition in groundwater as a paleoclimatic proxy assumes that the isotopic values in groundwater are inherited from the corresponding values in the source precipitation. However, several studies have observed that groundwater δ18O (δ18Og) is not always in accordance with the average δ18O of precipitation (δ18Op). The cause of this inconsistency is still the subject of debate. Significant reduced isotopic variability and potential deviations from precipitation to groundwater because of the aquifer itself (e.g., groundwater buried depths and soil texture) and external precipitation characteristics (e.g., rainfall intensity and duration) have been poorly quantified in terms of identifying the dominant factors. To investigate the controls on the transmission of isotopic signals from precipitation to groundwater, we present new stable isotope data for precipitation and groundwater from an experimental site using eight soil cylinders of different soil textures and burial depths in a monsoon region. We collected data at inter-event sampling intervals (30 min) during and after two heavy precipitation events (daily amounts higher than 10 mm). Our results demonstrated a significant disparity between the average isotopic values of heavy rainfall and light rainfall, despite both exhibiting decreasing isotopic patterns throughout the course of the rainfall event. Various degrees of attenuation of isotopic variations were found in outflow waters with different groundwater burial depths (GBDs) and soil textures after rainfall events. The isotopic variations were not synchronized with the outflow changes. Specifically, there were evident outflow lags in response to heavy rainfall, especially in the lysimeters with GBDs deeper than 0.5 m, while the greatest isotopic variation was observed in the early infiltrating stage. Redundancy analysis indicated that precipitation amount was the most important contributor to the outflow variation (∼51 %, p < 0.05), while GBD was the key factor for isotopic temporal variation (∼52 %, p < 0.05). These results concurred with the clustering of principal component analysis results. The mixing of soil water and heavy rainfall event components was observed in four lysimeters with mixing proportions fP varying in the range of 7 %–51 %, indicating the effective recharge from heavy rainfall. Soil evaporation was highlighted with samples located parallel to the local meteoric water line. It is recommended that groundwater isotopes in paleoclimatic studies are used with additional constraints that consider disproportionate recharge from intense rainfall, past chaotic fluctuations in groundwater dynamics, and distortions introduced by evaporation.

Response of soil water, salt, carbon and bacteria community to terrain and plant in coastal salt marsh

Terrain and plants play a crucial role in influencing or regulating the variations of water, salt, carbon, and bacteria community in the soil of coastal salt marshes. Investigating these variations and their interconnections under different conditions is essential to comprehensively understand the carbon sequestration function and reveal the underlying mechanisms of carbon sinks in coastal salt marshes. In this study, the various physicochemical properties of rhizosphere and non-rhizosphere soil under different terrain of coastal salt marsh in Jiaozhou Bay were determined. Additionally, the contents of soil carbon components including soil inorganic carbon (SIC), soil organic carbon (SOC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC), and constituents of soil dissolved organic matter (DOM) and microbial community were analyzed. The results showed that the contents of SIC and SOC in high-terrain soil were significantly lower than those in low-terrain soil (P < 0.05). Plants could regulate the physicochemical properties, and carbon components of soil in different terrain, resulting in no significant difference in SOC contents of rhizosphere soil under different terrain. Soil DOM composition and bacterial community showed that high-terrain soil had higher bacterial diversity and activity, and plants significantly affected the bacterial community structure in soil through rhizosphere effects. The structural equation model demonstrated that terrain has an indirect impact on SOC through influencing on the fluorescence of soil DOM and bacterial diversity, and SIC through altering soil water content (SWC), electrical conductivity and DOC. Plants directly or indirectly affected SOC content, and indirectly affected SIC content by changing SWC. This study contributes to a better understanding of the complex interactions between wetland ecosystems and their soil water, salt, carbon, and bacteria community components, offering valuable information for wetland management and conservation efforts.

Soil water components control plant water uptake along a subalpine elevation gradient on the Eastern Qinghai-Tibet Plateau

Soil water is crucial for maintaining forest health by providing plants with a dependable water source. However, the understanding of the impact of soil moisture on plant water uptake, particularly in conditions of excess soil water, is limited. In this study, we investigated root water uptake strategies of dominant species along an elevational gradient in the subalpine region of the eastern Qinghai–Tibet Plateau. Our results demonstrated divergent relationships between soil moisture and water uptake fractions in the shallow soil layer, where moisture generally exceeds field capacity (θfc) during the growing season, and in the deep soil layer, showing negative and positive associations, respectively. This disparity is linked to soil water components: when plants mainly used shallow soil water, the relative proportion of plant–available water (the part of water between wilting coefficient and θfc) in the shallow soil was smaller compared to instances where plants mainly used deep soil water. Conversely, the pattern for gravity water was the opposite. This phenomenon is attributed to precipitation replenishing shallow soil with gravity water and deep soil with plant–available water, leading to poor aeration in the shallow soil and an abundance of plant–available water in the deep soil, and plants tended to shift to deep soil water as a result. Furthermore, the decrease in the relative proportion of plant–available water in the shallow soil along the elevational gradient results in plants in the lowest-altitude broadleaf forest obtaining more shallow soil water and less deep soil water, which can also enhance our understanding of how soil moisture components influence plant water–use strategies. Additionally, no hydrological niche segregation was observed among species in this humid environment. These results can improve our comprehension of soil–plant interactions in subalpine areas.

Identification and quantification of soil water components in kaolin by thermogravimetric and kinetic analysis

Different types of soil water, such as bound water and capillary water, have distinct effects on the physicochemical and engineering properties of soils, particularly unsaturated clayey soils. Therefore, it is crucial to develop an accurate and physically meaningful experimental method for identifying and quantifying these components. This study pioneers the use of a multi-step kinetic model to identify and quantify different soil water components across a wide range of relative humidity (RH) using thermogravimetric analysis (TGA) data. To validate the determined kinetic parameters (i.e., activation energy, preexponential factor, and reaction model) and the identification and quantification results of soil water components, TGA with multiple heating rates, nitrogen adsorption method, cation exchange capacity measurement, and nuclear magnetic resonance (NMR) were performed on kaolin samples equilibrated under various RH conditions. These experimental results cross-validate the superior performance of the kinetic model in determining soil water components and predicting the thermal desorption behaviors of soil water. Based on the cross-validation results, the soil water components obtained from the kinetic analysis are further identified as tightly-bound, loosely-bound, and capillary water, which exhibit variations consistent with empirical soil water isotherm models. The T2 cutoff value between bound and capillary water is determined to be 1.79 ms based on TGA and NMR results. The determined thermal kinetic parameters of different soil water components can exhibit their distinct retention mechanisms. The method and results in this study provide a new perspective on identifying different soil water components, as well as understanding the mechanism of soil-water interactions in unsaturated soils.

Chemical characteristics and reactive transport of soil salt ions in frozen soil during the freeze and thaw period

Current researches on estimating soil salt movement during the freeze and thaw period are mainly based on total salt concentration, while ignoring the phase change of multi-component salts. In this study, the potential transport capability of soil water and salt ions in the frozen layer was investigated based on chemical characteristics and solute convection–diffusion theory. Field experiments were implemented to measure the change of total soil water, soil salt and its ion components. The soil water and salt content in liquid and solid phases were calculated by the FREZCHEM model, and then the movement of liquid soil water and soluble salt were simulated by the HYDRUS-1D model. The potential migration capability of soil water and salt components were then estimated by comparing the distribution profiles obtained by HYDRUS-1D and FREZCHEM. The results show that more than 74.5% of Cl, Na and SO4 were in liquid phase, which were less affected by precipitation-dissolution reaction and owned strong mitigation. The liquid soil water, soluble salt and salt ions in the frozen layer tended to decrease at the beginning of the freeze period and increase significantly at the end. The migration direction and quantity of various salt ions were different due to their concentration gradient and diffusion coefficient, causing the larger potential convection and dispersion quantity of Na+, Cl− and SO42- than those of Ca2+, Mg2+ and HCO3–. This study provides a new perspective for soil salt movement in frozen soil in agricultural areas with shallow groundwater table depth.

Inverted Algorithm of Groundwater Storage Anomalies by Combining the GNSS, GRACE/GRACE-FO, and GLDAS: A Case Study in the North China Plain

As the largest groundwater drainage region in China, the per capita water resources in the North China Plain (NCP) account for only one-seventh of the country’s available water resources. Currently, the NCP is experiencing a serious water shortage due to the overexploitation of groundwater resources and a subsequent series of natural disasters. Thus, accurate regional assessments and effective water resource management policies are of critical importance. To accomplish this phenomenon, the daily terrestrial water storage anomaly (TWSA) over the NCP is calculated from the combination of the GNSS vertical deformation sequences (seasonal items) and GRACE (trend items). The groundwater storage anomaly (GWSA) in the NCP is obtained by subtracting the canopy water, soil water, and snow water equivalent components from the TWSA. The inversion results of this study are verified by comparisons with the Global Land Data Assimilation System (GLDAS) data products. The elevated annual amplitude areas are located in Beijing and Tianjin, and the Pearson correlation coefficient (PCC), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE) between the two GWSA results are 0.67, 4.01 cm, and 0.61, respectively. This indicates that the methods proposed in this study are reliable. Finally, the groundwater drought index was calculated for the period from 2011 to 2021, and the results showed that 2019 was the driest year, with a drought severity index value of −0.12, indicative of slightly moderate drought conditions. By calculating and analyzing the annual GWSA, this work shows that the South–North Water Transfer Project does provide some regional drought mitigation.

Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation

CERES-Maize is a crop simulation model that can be applied as a tool to simulate grain yield, above-ground biomass, leaf area index (LAI), soil-water components (SWC), and other variables related to crop production. The model was calibrated and validated using long-term (2005–2010) field-measured data under full irrigation treatment (FIT), limited irrigation treatments (50%, 60% and 75% of FIT) and rainfed conditions in a transition zone between the subhumid and semi-arid climatic region in Nebraska, USA. Model performance was evaluated using the coefficient of determination (R2), absolute and normalized root mean squared errors (RMSE and RMSEn, respectively) between simulated and measured data. The RMSE between model-simulated and observed data for days after planting to flowering (DAPF) and maturity day (DAPM) were 3 and 13 days, respectively. There was an acceptable agreement between simulated and observed LAI (RMSEn = 17% and R2 = 0.79) and above-ground biomass (RMSEn = 16% and R2 = 0.95). Grain yield estimates by the model showed moderately high R2 (≥ 0.80) and moderate RMSEn (3–18%) values, confirming that the model simulated the grain yield accurately. The accuracy of the model in simulating SWC in FIT conditions was good, but with increasing water stress, the accuracy decreased. The cumulative drought stress index for photosynthesis (SIP) and drought stress index for leaf expansion (SIE) were also simulated and evaluated. There was an inverse relationship between grain yield and the SIP and SIE (R2 ≥ 0.97), indicating the potential applicability of SIP and SIE for estimating maize grain yield. Both SIP and SIE were strongly affected by the irrigation treatments. The FIT treatment had a value of 2 for cumulative SIE, indicating that this treatment was rarely exposed to drought/water stress. The results showed that irrigation and early planting date together had synergistic effects on grain yield. Delaying planting dates for the FIT led to yield reduction of 1%, 3% and 11% after planting dates of April 30, May 10 and May 20, respectively. Delay in planting date under rainfed led to greater yield reduction of 6%, 10% and 18% after planting dates of April 30, May 10 and May 20, respectively. The CERES-Maize model simulated maize crop parameters relatively accurately under rainfed, full and limited irrigation management conditions under the experimental and climatic conditions presented in this study and can be a viable tool for simulating various management scenarios for increasing maize productivity.

Resolving soil and surface water flux as drivers of pattern formation in Turing models of dryland vegetation: A unified approach

Over the past two decades, multi-component dryland vegetation models have been successful in qualitatively reproducing the spatial vegetation patterns widely observed in nature. In the two-component (water, vegetation) Klausmeier model, water flow from bare to vegetated areas drives pattern formation. The more elaborate Rietkerk and Gilad three-component models make a distinction between soil and surface water. In this article the three models are approximated from within a unifying framework, with a focus on processes that drive pattern formation, in order to promote the understanding of similarities and differences between these models. Reduction from a model with a separate soil and surface water component, to a model with a single water component, preserves Turing instability in all but one of the cases studied.

Runoff components of small catchments in Sikhote-Alin: summarizing the results of field measurements and tracer modeling

The article summarizes results of the systematic study of the streamflow formation of two small catchments in the upper part of the Ussuri River. The study was carried out by the hydrograph separation technique (using detailed data of the hydrochemical and hydrological monitoring) and the use of a tracer mixing model in conjunction with EMMA. Performed in the period from 2011 to 2016 the studies allowed to calculate the river runoff components of the summer-autumn period at 3 gauge-stations and evaluate their mutual dynamics at different time scales. It is shown that in the case of landscape uniformity of the catchment (the Medvezhiy Creek), the river flow can be represented as a result of 3 sources mixing. This, the most common, scheme for the hydrograph separation includes following sources: a direct rainfall flow, an organic soil water component, and an underground baseflow. If the catchments landscape structure is clearly heterogeneous (the Elovy Creek), the river flow can be represented as a result of 4 sources mixing. In this case, the fourth source appears as a result of the separation of soil water component into individual components organic and mineral. This separation is due to the spread in the basin of the cold upper belt of fir-spruce forests, whose soils are characterized by a lower rate of organic matter destruction and a deeper illuviation process of DOC. Statistically significant dependencies of the some runoff components proportions against river discharges were identified, systematization of which makes them promising for practice in hydrological monitoring and forecasting.

Multicomponent Satellite Assessment of Drought Severity in the Contiguous United States From 2002 to 2017 Using AMSR‐E and AMSR2

AbstractThe Advanced Microwave Scanning Radiometer for the Earth Observing System and Advanced Microwave Scanning Radiometer 2 sensors (AMSR) have provided multifrequency microwave measurements of the global terrestrial water cycle since 2002. A new AMSR surface wetness index (ASWI) was developed by analyzing the near‐surface atmospheric vapor pressure deficit (VPD), surface volumetric soil moisture (VSM), and land surface fractional open water (FW) time series from an established AMSR Land Parameter Data Record (LPDR). The ASWI allows for multicomponent and independent satellite assessments of near‐surface drought conditions by exploiting the weighted anomalies of VPD, VSM, and FW. Comparisons between ASWI and more traditional drought metrics, including the Palmer moisture anomaly index (PDSI‐Z) and the U.S. Drought Monitor, showed generally consistent classifications of drought severity for three major droughts over the Contiguous United States since 2002. The AWSI showed moderate (0.3 ≤ R ≤ 0.7 for 56% of area) to strong (R &gt; 0.7 for 29% of area) correlations with the PDSI‐Z during the summer months (June–August) from 2002 to 2017. ASWI and PDSI‐Z differences were attributed to AMSR retrieval uncertainties and the different aspects of drought represented by the indices. Comparisons between ASWI and the Gravity Recovery and Climate Experiment drought severity index (GRACE‐DSI) showed strong correspondence (R = 0.61) in regions where possible long‐term total water storage changes occurred. The sole reliance of the ASWI on satellite microwave remote sensing and continuing AMSR2 operations enables effective global monitoring of drought conditions while providing new information on the atmosphere, soil, and surface water components of drought.

Experimental Analysis and Empirical Model of the Complex Permittivity of Five Organic Soils at 1.4 GHz in the Temperature Range From −30 °C to 25 °C

The dielectric measurements were made for five organic soils taken from the tundra territories of Alaska, Yamal, and Taimyr, with the content of organic matter varying from 35% to 80%. The measurements were carried out in the temperature range from −30 °C to 25 °C, frequencies from 0.45 to 16 GHz and soil moisture from close to zero to the field moisture capacity. The refractive mixing model was applied to fit the measurements of the soil’s complex refractive index (CRI) as a function of soil moisture, with the values of temperature being fixed. As a result, a respective dielectric model was developed. The amounts of bound and transient water in the thawed and frozen soils were introduced as parameters of the developed model and derived as a function of temperature and content of soil organic matter. The other parameters which concern the CRIs of soil solids as well as bound, transient, and liquid soil water or ice components were derived as a function of temperature. The errors of the proposed model estimated in terms of the values of normalized root-mean-sqaure error for the real and imaginary parts of the soil complex relative permittivity appeared to be 6%–7% and 23%, respectively. The proposed dielectric model can be applied in active and passive remote sensing, in particular, for the SMOS, SMAP, and Aquarius missions after testing in ground-based experiments.

Determining groundwater recharge and vapor flow in dune sediments using a weighable precision meteo lysimeter

Dune belts are crucial for the recharge of coastal aquifers. In spite of their hydrological relevance for the maintenance of precious natural wetland and wildlife environments and a range of other ecosystem services, only limited knowledge of soil water dynamics in dune belts is currently available. This study presents soil water balance components measured during one hydrological year using a high precision meteo-lysimeter with lower boundary control installed in a coastal dune belt under a dry subhumid climate in southern Spain close to the Atlantic Ocean. The site is equipped with a cylindrical lysimeter of 1 m2 surface and 1.50 m height (METER Group, Inc. USA) and a weighing resolution of 10 g, 2 SC650 soil moisture sensors (Campbell Scientific, Logan, UT) and 1 automatic meteorological station. The lower boundary condition at the bottom of the lysimeter is controlled at 1.4 m depth by a bidirectional peristaltic pump to maintain field conditions. Results show a recharge rate of 64% of the precipitation measured by the lysimeter. Diurnal oscillations of the measured upper boundary flow during days without rainfall represented vapor adsorption and real evaporation rates ranging between 0.3 and 0.4 mm/day and 0.4 and 0.6 mm/day, respectively throughout the whole year summing up an annual vapor adsorption of 77 mm. The measured precipitation of the lysimeter exceeded pluviometer data by 13% as a result of vapor adsorption. The presented results provide a precise balance of soil water components in a coastal dune belt including the relevant contribution of vapor flow.

Development of the Moorepark St Gilles grass growth model (MoSt GG model): A predictive model for grass growth for pasture based systems

Abstract In humid-temperate regions grazed grass is the most economical means of feeding ruminant livestock. Grass growth is often highly variable and therefore difficult to predict. It is influenced by many factors including climatic conditions, soil type and soil nutrients. The Moorepark St. Gilles Grass Growth model (MoSt GG model) is a dynamic model developed in C++ describing daily grass growth at the paddock level. It was developed by adapting an existing grass growth model to include a nitrogen (N) component and a soil water component. The model is effective in grazing and cutting scenarios. Inputs include weather data, grazing management decisions and N fertiliser application. Outputs include daily grass growth, soil mineral N content, grass N uptake, grass N content and NO3− leaching. The MoSt GG model was evaluated against measured data using 2 years data from an experimental farm; the predicted and measured biomass for each paddock was compared. The mean root mean square prediction error (RMSPE) at the measurement level was 505 kg DM/ha. When averaged by week of year, the RMSPE was reduced to 321 kg DM/ha. The MoSt GG model was also evaluated against a range of management scenarios including N fertiliser application rate (from 0 to 650 kg N/ha per year) and defoliation management, and weather conditions. The grass growth response to N fertiliser application was, on average, 9.6 kg DM/kg N applied with a minimum response of 0.8 kg DM/kg N applied and a maximum response of 16.2 kg DM/kg N applied, which is in the range of previously published studies. The MoSt GG model responds to daily weather conditions, patterns and methods of sward defoliation, and describes daily variations in soil mineral and organic N content.

Joint studies of water phase transitions in Na-bentonite clay by calorimetric and dielectric methods

The present study consisted of an experimental investigation of phase transitions of soil water contained in moist Na-bentonite clay, using the differential scanning calorimetry (DSC) method, within the temperature range from −40 to 20 °C. Based on the results of DSC analysis, the following components of soil water were found in the frozen bentonite: non-freezing water, unfrozen water and ice. The proposed method of processing the obtained experimental calorimetric data allowed us to determine the temperature dependencies of the content of particular soil water components. Latent heat of fusion was found in two cases, namely: where the ice was transformed into bound or unbound unfrozen soil water. The results of the investigation into phase transitions, obtained via calorimetric measurements, were used to substantiate the method for studying the phase transitions of soil water by dielectric measurements. With this in mind, complex relative permittivity testing was conducted on the same moist Na-bentonite clay, in the temperature range from −30 to 0 °C and a gravimetric moisture range from the dry soil to 1 g/g. Based on the results of these dielectric tests and a refractive dielectric mixture model (RDMM), the following components of water were identified in the frozen soil: tightly bound water, loosely bound water, unbound water and ice. The dependences of the content of these components of soil water on the temperature were calculated. It was shown that the increase in the mass of unfrozen loosely bound water, as a result of a decrease in the ice mass, determined with dielectric measurements, is quantitatively consistent with the dependence calculated using calorimetric testing. This proves that the changes of the mass of the loosely bound water, determined by dielectric measurements, is a result of the phase transition and the corresponding temperature dependence can be used to determine the characteristics of these phase transitions.

Evidence for the Activation of Shallow Preferential Flow Paths in a Tropical Panama Watershed Using Germanium and Silicon

AbstractIn humid tropical watersheds, the hydrologic flow paths taken by rain event waters and how they interact with groundwater and soil matrix water to form streamflow are poorly understood. Preferential flow paths (PFPs) confound storm infiltration processes, especially in the humid tropics where PFPs are common. This work applies germanium (Ge) and silicon (Si) as natural flow path tracers in conjunction with water stable isotopes and electrical conductivity to examine the rapid delivery of shallow soil water, the activation of PFPs, and event water partitioning in an experimental catchment in central Panama. We employed a three‐component mixing model for hydrograph separation using the following end‐member waters: (i) base flow (high [Si], low [Ge], and low Ge/Si ratio), (ii) dilute canopy throughfall (low [Si] and low [Ge]), and (iii) shallow (&lt;15 cm) soil matrix water (low [Si], high [Ge], and high Ge/Si ratio). These three end‐members bounded all observed Ge/Si streamflow ratios. During small rain events (&lt;∼24 mm), base flow and dilute canopy throughfall components dominated stormflow. During larger precipitation events (&gt;∼35 mm), we detected the third shallow soil water component with an elevated [Ge] and Ge/Si ratio. This component reached its maximum during the hydrograph's receding limb coincident with the maximum event fraction, and increased proportionally to the total storm rainfall exceeding ∼35 mm. Only shallow (&lt;15 cm) soil matrix water exhibited elevated Ge concentrations and high Ge/Si ratios. This third component represents rapidly delivered soil matrix water combined with shallow lateral PFP activation through which event waters interact with soil minerals.

Discussion of “Development of Soil Moisture Drought Index to Characterize Droughts” by Mohammad M. Sohrabi, Jae H. Ryu, John Abatzoglou, and John Tracy

In the discussed paper, Sohrabi et al. presented a new drought index, termed soil moisture drought index (SODI), which is based on the difference between water supply and water demand [in other words, the moisture departure from the field capacity (FC) of soil] at a given site. The moisture departure [Eq. (1) in the discussed paper] used in SODI is the improved form of the moisture departure in Plamer Drought Severity Index (PDSI) [Eq. (17) in the discussed paper]. In the following, some cases presented in the discussed paper about SODI’s moisture departure are discussed: 1. There are some ambiguities in methodology of SODI’s moisture departure. Although the SODI is a two-layer soil-water balance model, the discussed paper has not clearly explained the relations of soil-water components between the first and second soil layers. Are these relations considered just like the Palmer approach when calculating the soil-water components of the moisture departure? 2. According to Eq. (1) of the discussed paper, when Pi > ðPEi þ SMDi−1Þ, the equation can simply be rewritten as Di 1⁄4 ROi þ ROi−1 ð1Þ where ROi (surface runoff in the current month) = Pi − ðPEi þ SMDi−1Þ; Pi = total precipitation; PEi = potential evapotranspiration; SMDi−1 = soil moisture deficiency; Di = moisture departure; and i = month number in the calendar year. All variables are expressed in terms of millimeters. Under this condition, the term Li (moisture loss from soil column in Eq. (1) of the discussed paper) is zero. Therefore, for the some successive high-precipitation months, the moisture departure may be calculated only based on sum of the surface runoffs in the current and previous months. There are two issues with Eq. (1) of this discussion paper: (1) the surface runoff in the previous month (ROi−1) is considered as important as the surface runoff in the current month (ROi), and (2) there is no upper limit for surface runoff and it is assumed that any value of surface runoff can be retained in soil column. The latter is unlike the PDSI, where the potential surface runoff is assumed to be the available water balance (AWC). The state where Pi < ðPEi þ SMDi−1Þ can be envisaged and anticipated to occur in a dry month, but the surface runoff in the previous month (ROi−1) is high enough to compensate the moisture deficiency in the current month. Such a state may be occurred due to the two previously mentioned issues. 3. In addition to the surface runoff, the soil moisture deficiency in the previous month (SMDi−1) is accounted for calculating the moisture departure in the current month. While the maximum value of SMDi−1 is considered AWC, there is no maximum value for ROi−1 in SODI’s moisture departure equation. This lead to the moisture departure series be strongly skewed, which in turn needs to be normalized by a proper transformation method such as that used in the discussed paper (i.e., Box-Cox transformation method). Box-Cox transformation should be used with caution in some cases because the transformed data may not be satisfactory even when the best value of transformation parameter had been chosen. There are some alternatives for BoxCox transformation such as Manly (1976) and Yeo and Johnson (2000), which can be used where the Box-Cox method is unable to satisfactorily convert nonnormal data to normal ones. The Manly transformation function is of the form

Benchmark data set for wheat growth models: field experiments and AgMIP multi-model simulations

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario. Data access via DOI 10.17026/DANS-ZB6-6FVQ.

Understanding runoff processes in a semi-arid environment through isotope and hydrochemical hydrograph separations

Abstract. The understanding of runoff generation mechanisms is crucial for the sustainable management of river basins such as the allocation of water resources or the prediction of floods and droughts. However, identifying the mechanisms of runoff generation has been a challenging task, even more so in arid and semi-arid areas where high rainfall and streamflow variability, high evaporation rates, and deep groundwater reservoirs may increase the complexity of hydrological process dynamics. Isotope and hydrochemical tracers have proven to be useful in identifying runoff components and their characteristics. Moreover, although widely used in humid temperate regions, isotope hydrograph separations have not been studied in detail in arid and semi-arid areas. Thus the purpose of this study is to determine whether isotope hydrograph separations are suitable for the quantification and characterization of runoff components in a semi-arid catchment considering the hydrological complexities of these regions. Through a hydrochemical characterization of the surface water and groundwater sources of the catchment and two- and three-component hydrograph separations, runoff components of the Kaap catchment in South Africa were quantified using both isotope and hydrochemical tracers. No major disadvantages while using isotope tracers over hydrochemical tracers were found. Hydrograph separation results showed that runoff in the Kaap catchment is mainly generated by groundwater sources. Two-component hydrograph separations revealed groundwater contributions of between 64 and 98 % of total runoff. By means of three-component hydrograph separations, runoff components were further separated into direct runoff, shallow and deep groundwater components. Direct runoff, defined as the direct precipitation on the stream channel and overland flow, contributed up to 41 % of total runoff during wet catchment conditions. Shallow groundwater defined as the soil water and near-surface water component (and potentially surface runoff) contributed up to 45 % of total runoff, and deep groundwater contributed up to 84 % of total runoff. A strong correlation for the four studied events was found between the antecedent precipitation conditions and direct runoff. These findings suggest that direct runoff is enhanced by wetter conditions in the catchment that trigger saturation excess overland flow as observed in the hydrograph separations.

A Temperature-Dependent Dielectric Model for Thawed and Frozen Organic Soil at 1.4 GHz

A single-frequency dielectric model for thawed and frozen Arctic organic-rich (80%–90% organic matter) soil was developed. The model is based on soil dielectric data that were measured over the ranges of volumetric moisture from 0.007 to ${0.573}\;\text{cm}^{{3}}/\text{cm}^{{3}}$ , dry soil density from 0.564 to $0.666\;\text{g/cm}^{3}$ , and temperature from 25 °C to $-\mathbf{30}^{\circ}\mathbf{C}$ (cooling run), at the frequency of 1.4 GHz. The refractive mixing model was applied to fit the measurements of the soil’s complex refractive index (CRI) as a function of soil moisture, with the values of temperature being fixed. Using the results of this fitting, the parameters of the refractive mixing model were derived as a function of temperature. These parameters involve the CRIs of soil solids as well as bound, transient, and free soil water components. The error of the dielectric model was evaluated by correlating the predicted complex relative permittivity (CRP) values of the soil samples with the measured ones. The coefficient of determination ( $\mathbf{R}^{\mathbf{2}}$ ) and the root-mean-square error (RMSE) were estimated to be $\mathbf{R}^{\mathbf{2}}= \mathbf{0.999}$ , $\mathbf{RMSE} = \mathbf{0.27}$ and $\mathbf{R}^{\mathbf{2}}= \mathbf{0.993}$ , $\mathbf{RMSE} = \mathbf{0.18}$ for the real and imaginary parts of the CRP, respectively. These values are in the order of the dielectric measurement error itself. The proposed dielectric model can be applied in active and passive remote-sensing techniques used in the areas with organic-rich soil covers, mainly for the SMOS, SMAP, and Aquarius missions.

A temperature-dependent multi-relaxation spectroscopic dielectric model for thawed and frozen organic soil at 0.05–15 GHz

A dielectric model for thawed and frozen Arctic organic-rich soil (50% organic matter) has been developed. The model is based on soil dielectric measurements that were collected over ranges of gravimetric moisture from 0.03 to 0.55g/g, dry soil density from 0.72 to 0.87g/cm3, and temperature from 25 to −30°C (cooling run) in the frequency range of 0.05–15GHz. The refractive mixing dielectric model was applied with the Debye multi-relaxation equations to fit the measurements of the soil’s complex dielectric constant as a function of soil moisture and wave frequency. The spectroscopic parameters of the dielectric relaxations for the bound, transient bound, and unbound soil water components were derived and were complimented by the thermodynamic parameters to obtain a complete set of parameters for the proposed temperature-dependent multi-relaxation spectroscopic dielectric model for moist soils. To calculate the complex dielectric constant of the soil, the following input variables must be assigned: (1) density of dry soil, (2) gravimetric moisture, (3) wave frequency, and (4) temperature. The error of the dielectric model was evaluated and yielded RMSEε′ values of 0.348 and 0.188 for the soil dielectric constant and the loss factor, respectively. These values are on the order of the dielectric measurement error itself. The proposed dielectric model can be applied in active and passive microwave remote sensing techniques to develop algorithms for retrieving the soil moisture and the freeze/thaw state of organic-rich topsoil in the Arctic regions.