From precipitation to runoff: stable isotopic fractionation effect of glacier melting on a catchment scale

Stable isotope variability and fractionation associated with transformation of precipitation/accumulation to firn to glacial river water is critical in a variety of climatic, hydrological and paleoenvironmental studies. This paper documents the modification of stable isotopes in water from precipitation to glacier runoff in an alpine catchment located in the central Tibetan Plateau. Isotopic changes are observed by sampling firnpack profiles, glacier surface snow/ice, meltwater on the glacier surface and catchment river water at different times during a melt season. Results show the isotopic fractionation effects associated with glacier melt processes. The slope of the δD‐δ¹⁸O regression line and the deuterium excess values decreased from the initial precipitation to the melt‐impacted firnpack (slope from 9.3 to 8.5 and average d‐excess from 13.4‰ to 7.4‰). The slope of the δD‐δ¹⁸O line further decreased to 7.6 for the glacier runoff water. The glacier surface snow/ice from different locations, which produces the main runoff, had the same δD‐δ¹⁸O line slope but lower deuterium excess (by 3.9‰) compared to values observed in the firnpack profile during the melt season. The δD‐δ¹⁸O regression line for the river water exhibited a lower slope compared to the surface snow/ice samples, although they were closely located on the δD‐δ¹⁸O plot. Isotope values for the river and glacier surface meltwater showed little scatter around the δD‐δ¹⁸O regression line, although the samples were from different glaciers and were collected on different days. Results indicate a high consistency of isotopic fractionation in the δD‐δ¹⁸O relationships, as well as a general consistency and temporal covariation of meltwater isotope values at the catchment scale. Copyright © 2013 John Wiley & Sons, Ltd.     

Agricultural management impacts on groundwater: simulations of existing and alternative management options in Peninsular India

Understanding the principal causes and possible solutions for groundwater depletion in India is important for its water security, especially as it relates to agriculture. A study was conducted in an agricultural watershed in Andhra Pradesh, India to assess the impacts on groundwater of current and alternative agricultural management. Hydrological simulations were used as follows: (1) to evaluate the recharge benefits of water‐harvesting tillage through a modified Soil and Water Assessment Tool (SWAT) model and (2) to predict the groundwater response to changing extent and irrigation management of rice growing areas. The Green–Ampt infiltration routine was modified in SWAT was modified to represent water‐harvesting tillage using maximum depression storage parameter. Water‐harvesting tillage in rainfed croplands was shown to increase basin‐scale groundwater recharge by 3% and decrease run‐off by 43% compared with existing conventional tillage. The groundwater balance (recharge minus irrigation withdrawals), negative 11 mm/year under existing management changed to positive (18–45 mm/year) when rice growing areas or irrigation depths were reduced. Groundwater balance was sensitive to changes in rice cropland management, meaning even small changes in rice cropland management had large impacts on groundwater availability. The modified SWAT was capable of representing tillage management of varying maximum depression storage, and tillage for water‐harvesting was shown to be a potentially important strategy for producers to enhance infiltration and groundwater recharge, especially in semi‐arid regions where rainfall may be becoming increasingly variable. This enhanced SWAT could be used to evaluate the landscape‐scale impacts of alternative tillage management in other regions that are working to develop strategies for reducing groundwater depletion. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of river channel geometry in stream flow modelling and guidelines for field investigation

Fully physics‐based, process‐level, distributed fluid flow and reactive transport hydrological models are rarely used in practice until recent years. These models are useful tools to help understand the fundamental physical, chemical, and biological processes that take place in nature. In this study, sensitivity analyses based on a mountain area river basin modelling study are performed to investigate the effect of river channel geometric characteristics on downstream water flow. Numerical experiments show that reduction in the river channel geometric measurement interval may not significantly affect the downstream water stage simulation as long as measurement accuracy at special nodes is guaranteed. The special upstream nodes include but are not limited to 1) nodes located close to the observation station, 2) nodes near the borders of different land covers with considerable riverbed roughness changes, 3) nodes at entering points of tributaries causing discharge jump and 4) nodes with a narrow cross‐section width that may control the flow conditions. This information provides guidelines for field investigation to efficiently obtain necessary geometric data for physics‐based hydrological modelling. It is especially useful in alpine areas such as the Tibetan Plateau where field investigation capability is limited under severe topography and climate condition. Copyright © 2013 John Wiley & Sons, Ltd.     

Eigenvector selection with stepwise regression techniques to construct eigenvector spatial filters

Because eigenvector spatial filtering (ESF) provides a relatively simple and successful method to account for spatial autocorrelation in regression, increasingly it has been adopted in various fields. Although ESF can be easily implemented with a stepwise procedure, such as traditional stepwise regression, its computational efficiency can be further improved. Two major computational components in ESF are extracting eigenvectors and identifying a subset of these eigenvectors. This paper focuses on how a subset of eigenvectors can be efficiently and effectively identified. A simulation experiment summarized in this paper shows that, with a well-prepared candidate eigenvector set, ESF can effectively account for spatial autocorrelation and achieve computational efficiency. This paper further proposes a nonlinear equation for constructing an ideal candidate eigenvector set based on the results of the simulation experiment.     

The role of rainfall temporal and spatial averaging in seasonal simulations of the terrestrial water balance

The partitioning of rainfall into surface runoff and infiltration influences many other aspects of the hydrologic cycle including evapotranspiration, deep drainage and soil moisture. This partitioning is an instantaneous non-linear process that is strongly dependent on rainfall rate, soil moisture and soil hydraulic properties. Though all rainfall datasets involve some degree of spatial or temporal averaging, it is not understood how this averaging affects simulated partitioning and the land surface water balance across a wide range of soil and climate types. We used a one-dimensional physics-based model of the near-surface unsaturated zone to compare the effects of different rainfall discretization (5-min point-scale; hourly point-scale; hourly 0.125° gridded) on the simulated partitioning of rainfall for many locations across the United States. Coarser temporal resolution rainfall data underpredicted seasonal surface runoff for all soil types except those with very high infiltration capacities (i.e., sand, loamy sand). Soils with intermediate infiltration capacities (i.e., loam, sandy loam) were the most affected, with less than half of the expected surface runoff produced in most soil types when the gridded rainfall dataset was used as input. The impact of averaging on the water balance was less extreme but non-negligible, with the hourly point-scale predictions exhibiting median evapotranspiration, drainage and soil moisture values within 10% of those predicted using the higher resolution 5-min rainfall. Water balance impacts were greater using the gridded hourly dataset, with average underpredictions of ET up to 27% in fine-grained soils. The results suggest that “hyperresolution” modelling at continental to global scales may produce inaccurate predictions if there is not parallel effort to produce higher resolution precipitation inputs or sub-grid precipitation parameterizations.     

Predicting evaporation from mountain streams

Evaporation can be an important control on stream temperature, particularly in summer when it acts to limit daily maximum stream temperature. Evaporation from streams is usually modelled with the use of a wind function that includes empirically derived coefficients. A small number of studies derived wind functions for individual streams; the fitted parameters varied substantially among sites. In this study, stream evaporation and above-stream meteorological conditions (at 0.5 and 1.5 m above the water surface) were measured at nine mountain streams in southwestern British Columbia, Canada, covering a range of stream widths, temperatures, and riparian vegetation. Evaporation was measured on 20 site-days in total, at approximately hourly intervals, using nine floating evaporation pans distributed across the channels. The wind function was fit using mixed-effects models to account for among-stream variability in the parameters. The fixed-effects parameters were tested using leave-one-site-out cross-validation. The model based on 0.5 m measurements provided improved model performance compared to that based on 1.5 m values, with RMSE of 0.0162 and 0.0187 mm h⁻¹, respectively, relative to a mean evaporation rate of 0.06 mm h⁻¹. Inclusion of atmospheric stability and canopy openness as predictors improved model performance when using the 1.5 m meteorological measurements, with minimal improvement when based on 0.5 m measurements. Of the wind functions reported in the literature, two performed reasonably while five others exhibited substantial bias.