Using hydrogeochemical signatures of stream water to assess pathways for rainfall events: towards a predictive model

Thanks to its simple division into agricultural and forestry land use, the Corbeira catchment (Galicia, Spain) is used as a case study to build a predictive model using hydrogeochemical signatures. Stream data acquired under recessional flow conditions over a one year period were obtained from a sampling station near the downstream end of the catchment, and using principal component analysis, it is shown that some of the analytical parameters are covariant, and some are negatively correlated. These findings support inferences about the pathways of rainfall in the catchment. Specific signatures may be associated with the dominant hydrological source, either surface runoff or subsurface waters: additionally, the dominant land use in that part of the catchment, where the flow originated, can also be predicted. The dominant runoff shows a strong covariance between suspended solids (SS) and particulate phosphorus (PP), with a clear negative correlation with pH. Dissolved organic carbon (DOC) data are associated with this covariant set when these compounds are available in the soils in question. Dissolved phosphorus, total organic nitrogen and dissolved nitrates are also associated with the same covariant set when the runoff flows through areas of extensive agricultural use. The SS ? PP covariance is less significant at lower flows. Typical base flow regimes show a significant covariance between salinity and pH, with a marked negative correlation with SS ? PP set, confirming the dominance of subsurface waters in the baseflow, as expected. Seasonally divergent DOC ? SS behaviour proves to be a useful tracer for rainfall regimes. The DOC trend shows a sinusoidal annual variation in amplitude, determined by the rainfall regime. As a result, flow from the catchment is dominated by surface water whenever there is synchronicity between the peaks of DOC and SS. Copyright © 2013 John Wiley & Sons, Ltd.     

A probabilistic approach for computing water retention of particulate systems from statistics of grain size and tessellated pore network

The paper offers an analytical determination of the hydraulic properties of an unsaturated soil with reference to its retention curve, which describes the relationship between the volumetric water content and capillarity through matric suction. The analysis combines a particulate approach focused on the physics at the pore scale, including microstructural aspects, with a probabilistic approach where the void space and grain size are considered as random variables. In the end, the soil water characteristic curve of an unsaturated granular medium along a drying path can be derived analytically based on the sole information of particle size distribution. The analysis hinges on the tessellation of a wet granular system into an assemblage of tetrahedral unit cells revealing a pore network upon which capillary physics are computed with respect to pore throat invasion by a non-wetting fluid with evolving pendular capillary bridges. The crux of the paper is to pass from particle size probability distribution to a matching void space distribution to eventually reveal key information such as void cell and solid volume statistics. Making reasonable statistically based assumptions to render calculations tractable, the water retention curve can be readily constructed. Model predictions compare quite favourably with experimental data available for actual soils, especially in the high saturation range. Having a sound scientific basis, the model can be made amenable to address a variety of soils with a wider range of particle sizes.     

A hydropedological approach to simulate streamflow and soil water contents with SWAT+

Reflecting internal catchment hydrological processes in hydrological models is important for accurate predictions of the impact of climate and land-use change on water resources. Characterizing these processes is however difficult and expensive due to their dynamic nature and spatio-temporal variability. Hydropedology is a relatively new discipline focusing on the synergistic integration of hydrology, soil physics and pedology. Hydropedological interpretations of soils and soil distribution can be used to characterize key hydrological processes, especially in areas with no or limited hydrometric measurements. Here we applied a hydropedological approach to reflect flowpaths through detailed routing in SWAT+ for a 157 ha catchment (Weatherley) in South Africa. We compared the hydropedological approach and a standard (no routing) approach against measured streamflow (two weirs) and soil water contents (13 locations). The catchment was treated as ‘ungauged’ and the model was not calibrated against hydrometric measurements in order to determine the direct contribution of hydropedology on modelling efficiency. Streamflow was predicted well without calibration (NSE > 0.8; R² > 0.82) for both approaches at both weirs. The standard approach yielded slightly better streamflow predictions. The hydropedological approach resulted in considerable improvements in the simulation of soil water contents (R² increased from 0.40 to 0.49 and PBIAS decreased from 40% to 20%). The routing capacity of SWAT+ as employed in the hydropedological approach reduced the underestimation of wetland water regimes drastically and resulted in a more accurate representation of the dominant hydrological processes in this catchment. We concluded that hydropedology can be a valuable source of ‘soft data’ to reflect internal catchment structure and processes and, potentially, for realistic calibrations in other studies, especially those conducted in areas with limited hydrometric measurements.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.     

Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

An analytical approach to ascertain saturation‐excess versus infiltration‐excess overland flow in urban and reference landscapes

Uncontrolled overland flow drives flooding, erosion, and contaminant transport, with the severity of these outcomes often amplified in urban areas. In pervious media such as urban soils, overland flow is initiated via either infiltration‐excess (where precipitation rate exceeds infiltration capacity) or saturation‐excess (when precipitation volume exceeds soil profile storage) mechanisms. These processes call for different management strategies, making it important for municipalities to discern between them. In this study, we derived a generalized one‐dimensional model that distinguishes between infiltration‐excess overland flow (IEOF) and saturation‐excess overland flow (SEOF) using Green–Ampt infiltration concepts. Next, we applied this model to estimate overland flow generation from pervious areas in 11 U.S. cities. We used rainfall forcing that represented low‐ and high‐intensity events and compared responses among measured urban versus predevelopment reference soil hydraulic properties. The derivation showed that the propensity for IEOF versus SEOF is related to the equivalence between two nondimensional ratios: (a) precipitation rate to depth‐weighted hydraulic conductivity and (b) depth of soil profile restrictive layer to soil capillary potential. Across all cities, reference soil profiles were associated with greater IEOF for the high‐intensity set of storms, and urbanized soil profiles tended towards production of SEOF during the lower intensity set of storms. Urban soils produced more cumulative overland flow as a fraction of cumulative precipitation than did reference soils, particularly under conditions associated with SEOF. These results will assist cities in identifying the type and extent of interventions needed to manage storm water produced from pervious areas.     

Seasonal variations in infiltrability of moss‐dominated biocrusts on aeolian sand and loess soil in the Chinese Loess Plateau

Biocrust effects on soil infiltration have attracted increasing attention in dryland ecosystems, but their seasonal variations in infiltrability have not yet been well understood. On the Chinese Loess Plateau, soil infiltrability indicated by saturated hydraulic conductivity (K_s) of biocrusts and bare soil, both on aeolian sand and loess soil, was determined by disc infiltrometer in late spring (SPR), midsummer (SUM), and early fall (FAL). Then their correlations with soil biological and physiochemical properties and water repellency index (RI) were analysed. The results showed that the biocrusts significantly decreased K_s both on sand during SPR, SUM, and FAL (by 43%, 66%, and 35%, respectively; P < .05) and on loess (by 42%, 92%, and 10%, respectively; P <.05). As compared with the bare soil, the decreased K_s in the biocrusted surfaces was mostly attributed to the microorganism biomass and also to the increasing content of fine particles and organic matter. Most importantly, both the biocrusts and bare soil exhibited significant (F ≥ 11.89, P ≤ .003) seasonal variations in K_s, but their patterns were quite different. Specifically, the K_s of bare soil gradually decreased from SPR to SUM (32% and 42% for sand and loess, respectively) and FAL (29% and 39%); the K_s of biocrusts also decreased from SPR to SUM (59% and 92%) but then increased in FAL (36% and 588%). Whereas the seasonal variations in K_s of the biocrusts were closely correlated with the seasonal variations in RI, the RI values were not high enough to point at hydrophobicity. Instead of that, the seasonal variations of K_s were principally explained by the changes in the crust biomass and possibly by the microbial exopolysaccharides. We conclude that the biocrusts significantly decreased soil infiltrability and exhibited a different seasonal variation pattern, which should be carefully considered in future analyses of hydropedological processes.     

Bound and mobile soil water isotope ratios are affected by soil texture and mineralogy,whereas extraction method influences their measurement

Questions persist about interpreting isotope ratios of bound and mobile soil water pools, particularly relative to clay content and extraction conditions. Interactions between pools and resulting extracted water isotope composition are presumably related to soil texture, yet few studies have manipulated the bound pool to understand its influence on soil water processes. Using a series of drying and spiking experiments, we effectively labelled bound and mobile water pools in soils with varying clay content. Soils were first vacuum dried to remove residual water, which was then replaced with heavy isotope-enriched water prior to oven drying and spiking with heavy isotope-depleted water. Water was extracted via centrifugation or cryogenic vacuum distillation (at four temperatures) and analysed for oxygen and hydrogen isotope ratios via isotope ratio mass spectrometry. Water from centrifuged samples fell along a mixing line between the two added waters but was more enriched in heavy isotopes than the depleted label, demonstrating that despite oven drying, a residual pool remains and mixes with the mobile water. Soils with higher clay + silt content appeared to have a larger bound pool. Water from vacuum distillation samples have a significant temperature effect, with high temperature extractions yielding progressively more heavy isotope-enriched values, suggesting that Rayleigh fractionation occurred at low temperatures in the vacuum line. By distinctly labelling bound and mobile soil water pools, we detected interactions between the two that were dependent on soil texture. Although neither extraction method appeared to completely extract the combined bound and mobile (total water) pool, centrifugation and high temperature cryogenic vacuum distillations were comparable for both δ²H and δ¹⁸O of soil water isotope ratios.     

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.     

Spatio‐temporal variability of the isotopic input signal in a partly forested catchment: Implications for hydrograph separation

The isotopic composition of precipitation (D and ¹⁸O) has been widely used as an input signal in water tracer studies. Whereas much recent effort has been put into developing methodologies to improve our understanding and modelling of hydrological processes (e.g., transit‐time distributions or young water fractions), less attention has been paid to the spatio‐temporal variability of the isotopic composition of precipitation, used as input signal in these studies. Here, we investigated the uncertainty in isotope‐based hydrograph separation due to the spatio‐temporal variability of the isotopic composition of precipitation. The study was carried out in a Mediterranean headwater catchment (0.56 km²). Rainfall and throughfall samples were collected at three locations across this relatively small catchment, and stream water samples were collected at the outlet. Results showed that throughout an event, the spatial variability of the input signal had a higher impact on hydrograph separation results than its temporal variability. However, differences in isotope‐based hydrograph separation determined preevent water due to the spatio‐temporal variability were different between events and ranged between 1 and 14%. Based on catchment‐scale isoscapes, the most representative sampling location could also be identified. This study confirms that even in small headwater catchments, spatio‐temporal variability can be significant. Therefore, it is important to characterize this variability and identify the best sampling strategy to reduce the uncertainty in our understanding of catchment hydrological processes.