Hydrological Processes

Zhang, Fan; Xiao, Xiong; Wang, Lijie; Zeng, Chen; Yu, Zhengliang; Wang, Guanxing; Shi, Xiaonan

doi: 10.1002/hyp.14330pmid: N/A

Climate factors play critical roles in controlling chemical weathering, while chemically weathered surface material can regulate climate change. To estimate global chemical weathering fluxes and CO2 balance, it is important to identify the characteristics and driving factors of chemical weathering and CO2 consumption on the Tibetan Plateau, especially in glaciated catchments. The analysis of the hydro‐geochemical data indicated that silicate weathering in this area was inhibited by low temperatures, while carbonate weathering was promoted by the abundant clastic rocks with fresh surfaces produced by glacial action. Carbonate weathering dominated the riverine solute generation (with a contribution of 58%, 51%, and 43% at the QiangYong Glacier (QYG), the WengGuo Hydrological Station (WGHS), and the lake estuary (LE), respectively). The oxidation of pyrite contributed to 35%, 42%, and 30% of the riverine solutes, while silicate weathering contributed to 5%, 6%, and 26% of the riverine solutes at the QYG, WGHS, and LE, respectively. The alluvial deposit of easily weathering fine silicate minerals, the higher air temperature, plant density, and soil thickness at the downstream LE in comparison to upstream and midstream may lead to longer contact time between pore water and mineral materials, thus enhancing the silicate weathering. Because of the involvement of sulfuric acid produced by the oxidation of pyrite, carbonate weathering in the upstream and midstream did not consume atmospheric CO2, resulting in the high rate of carbonate weathering (73.9 and 75.6 t km−2 yr−1, respectively, in maximum) and potential net release of CO2 (with an upper constraint of 35.6 and 35.2 t km−2 yr−1, respectively) at the QYG and WGHS. The above results indicate the potential of the glaciated area of the Tibetan Plateau with pyrite deposits being a substantial natural carbon source, which deserves further investigation.

Raczyński, Krzysztof; Dyer, Jamie

doi: 10.1002/hyp.14322pmid: N/A

This paper presents a scheme describing low flow formation processes in areas with different environmental conditions, including the impact of the selection and explanatory power of predictors for a probabilistic model based on the Logit model. The research was carried out using 29 daily streamflow gauges located in the Lublin region of southeastern Poland for the hydrological period 1976–2018. Analysis resulted in two distinct low flow schemes. In the lowland rivers, low flows occur during the warm season and are related to evaporation exceeding precipitation. In the upland rivers, hydrogeological factors related to water levels in the local Cretaceous aquifers determine the occurrence of low flows. This differentiation affects the quality of the predictive models. For lowland rivers, models based on the climatic water balance with a monthly shift have a better fit, while these models used for upland rivers are characterized by an approximately 10% decrease in accuracy. For upland rivers, the combined CtHt models without shifts produce the best model fit. The generalized precision of the Logit models is around 80%–90%.

Beltran, Julio; Lautz, Laura K.; Slosson, John R.

doi: 10.1002/hyp.14324pmid: N/A

Urbanization negatively impacts water quality in streams by reducing stream‐groundwater interactions, which can reduce a stream's capacity to naturally attenuate nitrate. Meadowbrook Creek, a first order urban stream in Syracuse, New York, has an inverse urbanization gradient, with heavily urbanized headwaters that are disconnected from the floodplain and downstream reaches that have intact riparian floodplains and connection to riparian aquifers. This system allows assessment of how stream‐groundwater interactions in urban streams impact the net sources and sinks of nitrate at the reach scale. We used continuous (15‐min) streamflow measurements and weekly grab samples at three gauging stations positioned longitudinally along the creek to develop continuous nitrate load estimates at the inlet and outlet of two contrasting reaches. Nitrate load estimates were determined using a USGS linear regression model, RLOADEST, and differences between loads at the inlet and outlet of contrasting reaches were used to quantify nitrate sink and source behaviour year‐round. We observed a nitrate load of 1.4 × 104 kg NO3− per water year, on average, at the outlet of the urbanized reach while the nitrate load at the outlet of the downstream, connected reach was 1.0 × 104 kg NO3− per water year, on average. We found the more heavily urbanized, hydrologically‐disconnected reach was a net source of nitrate regardless of season. In contrast, stream‐groundwater exchange caused the hydrologically connected reach to be both a source and sink for nitrate, depending on time of year. Both reaches alter nitrate source and sink behaviour at various spatiotemporal scales. Groundwater connection in the downstream, connected reach reduces annual nitrate loads and provides more opportunities for sources and sinks of nitrate year‐round than the hydrologically disconnected stream reach. Mechanisms include groundwater discharge into the stream with variable nitrate concentrations, surface‐water groundwater interactions that foster denitrification, and stream load loss to surrounding near‐stream aquifers. This study emphasizes how loads are important in understanding how stream‐groundwater interactions impact reach scale nitrate export in urban streams.

Farran, Mohammed M.; Al‐Amri, Nassir; Elfeki, Amro M.

doi: 10.1002/hyp.14318pmid: N/A

Estimation of the infiltration/natural recharge to groundwater from rainfall is an important issue in hydrology, particularly in arid regions. This paper proposes the application of The Natural Resources Conservation Service (NRCS) mass balance model to develop infiltration (F)–rainfall (P) relationship from flash flood events. Moreover, the NRCS method is compared with the rational and the Ф‐index methods to investigate the discrepancies between these methods. The methods have been applied to five gauged basins and their 19 sub‐basins (representative basins with detailed measurements) in the southwestern part of Saudi Arabia with 161 storms recorded in 4 years. The F–P relationships developed in this study based on NRCS method are: F = 39% P with R2 = 0.932 for the initial abstraction factor, λ = 0.2. However, F = 77% P with R2 = 0.986 for λ = 0.01. The model at λ = 0.01 is the best to fit the data, therefore, it is recommended to use the formula at λ = 0.01. The results show that the NRCS model is appropriate for the estimation of the F–P relationships in arid regions when compared with the rational and the Ф index methods. The latter overestimates the infiltration because they do not take λ into account. There is no significant difference between F–P relationships at different time scales. This helps the prediction of infiltration rates for aquifer recharge at ungauged basins from monthly and annual rainfall data with a single formula.

Reichert, José Miguel; de Deus Junior, José Carlos; Borges Junior, Norton; Cavalcante, Rosane Barbosa Lopes

doi: 10.1002/hyp.14285pmid: N/A

The introduction of exotic, fast‐growing forest species in the Pampa biome (Southern Grasslands) is a controversial topic, considering the potential effect on water and soil resources. This repository contains hydrologic data (rainfall, discharge and turbidity) collected since 2011 in three small (≤1.1 km2), paired experimental catchments of the “Ponta da Canas” site, in the Pampa biome in subtropical Brazil. Two catchments are predominantly covered with eucalyptus plantations, and one with livestock‐grazing degraded grassland. For each catchment, the collected data include 10‐min resolution rainfall, streamflow, and turbidity (except for one of the eucalyptus catchments), automatically recorded in 10‐min intervals. In each catchment, rainfall is measured with an automatic tipping‐bucket rain gauge; stream depth is determined with a pressure transducer at the spillway, and a rating curve is used to estimate discharge; and turbidity is measured with a turbidimeter. The collected data are being used to understand water balance and sediment production under the distinct land uses, to improve forest management, and comply with State legislation.

Xue, Jingya; Zhao, Zhonghua; Yao, Xiaolong; Liu, Weiting; Zhang, Lu

doi: 10.1002/hyp.14345pmid: N/A

Many large rivers worldwide are enriched with high levels of suspended solids (SS), which are known to be hotspots of many nitrogen (N) transformation processes (e.g., denitrification, nitrification). However, the influence of SS on microbial ammonium (NH4+) recycling remains unclear. Water column NH4+ regeneration rates (REGs) and potential uptake rates (Upots) as well as community biological NH4+ demand (CBAD) was measured in the river‐estuary continuum of the third longest river in the world—Yangtze River, which has dramatic SS gradients. We found that REGs, Upots, and CBAD all increased downriver, with higher REGs, Upots, and CBAD in the estuary than in the river sections. The regeneration and uptake of NH4+ were nearly balanced in the river sections, while the positive CBAD in the estuary indicated obvious NH4+ demand of microbes. Concentrations of SS, which also control the content of chemical oxygen demand and particulate N, were the main factor influencing NH4+ recycling rates and CBAD. SS‐induced regenerated NH4+ in the river‐estuary continuum of Yangtze River was estimated to be 11.02 × 108 kg N yr−1 and accounted for about 14% of total N inputs, suggesting that regenerated NH4+ is an important N source for microbes and may influence nutrient dynamics in lower coasts. To our knowledge, this is the first study to report NH4+ recycling in Yangtze River with an emphasis on its influencing factors and contribution to N budgets.

Jutglar, Karuna; Hellwig, Jost; Stoelzle, Michael; Lange, Jens

doi: 10.1002/hyp.14307pmid: N/A

Elevated nitrate concentrations in groundwater are a common challenge for water management. One important factor in this context is higher frequencies and intensities of wet‐dry cycles that may cause increased nitrate concentrations in groundwater due to nitrate flushes after drought termination. Yet systematic studies on regional‐scale impacts of droughts on groundwater nitrate concentrations are missing so far. Here we analyzed time series of 44 shallow groundwater wells and 41 springs all across the German Federal State Baden‐Wuerttemberg from 2000 to 2018 to characterize patterns of post‐drought nitrate increase in groundwater. In general, half of the exceptional nitrate concentrations, which exceeded the 80th percentile of long‐term nitrate measurements, could be related to droughts in the research timeframe. The 2003 drought event stood out in terms of drought severity and post‐drought nitrate concentration increases in our data. The great majority (91%) of all monitoring sites showed at least one exceptionally high nitrate concentration in the 4 years following the 2003 drought event. Springs were mainly located in forests of steep low mountain ranges and wells in cropland of flat river valleys. Therefore, delay times between drought intensity and nitrate concentration increases as well as magnitudes of nitrate concentration increase were diverse among wells and springs. We derived two distinct nitrate response patterns: (i) nitrate increases immediately following drought events (more common for springs and fractured rock aquifers) and (ii) delayed nitrate increases (more common for wells and porous aquifers). Springs generally showed quicker (median of 101 days) but weaker (median of +1.3 mg/L) post‐drought nitrate increases than wells (185 days, +3.4 mg/L). Only few sites exhibited no post‐drought nitrate increase and post‐drought mean‐nitrate concentrations of groundwater reservoirs were extraordinarily high in 2006. Overall, we demonstrate that post‐drought nitrate increase in groundwater is omnipresent, while different landscapes and hydrogeological characteristics create a diverse regional pattern. As severe droughts become more frequent in a changing climate, post‐drought nitrate increase may intensify problems regarding water quality and supply.

doi: 10.1002/hyp.13816pmid: N/A

Hou, Jinliang; Huang, Chunlin; Chen, Weijing; Zhang, Ying

doi: 10.1002/hyp.14303pmid: N/A

A snow depletion curve (SDC), the relationship between snow mass (e.g., snow depth [SD]) and fractional snow cover area (SCF), is essential to parameterize the effect of snowpack within a physically based snow model. Existing SDCs are constructed using traditional statistic methods may not be applicable in complex mountainous areas. In this study, we developed an information fusion framework to define the relationship between SCF and SD as well as 12 auxiliary factors by using a traditional statistical method and four prevailing machine learning (ML) algorithms, which have comprehensively considered the variable conditions that cause spatiotemporal heterogeneity of snow cover. We also performed a single‐dimensional sensitivity analysis to investigate the physical rationality of the newly developed SDCs. The Northern Xinjiang, Northwest China, is selected as the study area, and the data from 46 meteorological stations covering five snow seasons from 2010 to 2015 are used. The results illustrated that ML techniques can be used to establish high‐accuracy and robust SDCs for complex mountainous areas. Compared with SDCs constructed by traditional statistical, the performance of the four ML‐based SDCs is significantly improved, the RMSE values can be reduced by 50%, R2 above 0.75, and an average relative variance close to 0. ML‐based SDCs predicted SCF values showed a range of sensitivities to different input variables (e.g., Land surface temperature, aspect, longwave radiation and land cover type), in addition to SD, that were physically representative of effects that snow cover is sensitive to. Moreover, the complexity of SDCs can be reduced by removing insensitive input variables.

Jackson, Faye L.; Hannah, David M.; Ouellet, Valerie; Malcolm, Iain A.

doi: 10.1002/hyp.14314pmid: N/A

Increasing river temperatures are a threat to cold water species including ecologically and economically important freshwater fish, such as Atlantic salmon. In 2018, ca. 70% of Scottish rivers experienced temperatures which cause thermal stress in juvenile salmon, a situation expected to become increasingly common under climate change. Management of riparian woodlands is proven to protect cold water habitats. However, creation of new riparian woodlands can be costly and logistically challenging. It is therefore important that planting can be prioritized to areas where it is most needed and can be most effective in reducing river temperatures. The effects of riparian woodland on channel shading depend on complex interactions between channel width, orientation, aspect, gradient, tree height and solar geometry. Subsequent effects on river temperature are influenced by water volume and residence time. This study developed a deterministic river temperature model, driven by energy gains from solar radiation that are modified by water volume and residence time. The resulting output is a planting prioritization metric that compares potential warming between scenarios with and without riparian woodland. The prioritization metric has a reach scale spatial resolution, but can be mapped at large spatial scales using information obtained from a digital river network. The results indicate that water volume and residence time, as represented by river order, are a dominant control on the effectiveness of riparian woodland in reducing river temperature. Ignoring these effects could result in a sub‐optimal prioritization process and inappropriate resource allocation. Within river order, effectiveness of riparian shading depends on interactions between channel and landscape characteristics. Given the complexity and interacting nature of controls, the use of simple universal planting criteria is not appropriate. Instead, managers should be provided with maps that translate complex models into readily useable tools to prioritize riparian tree planting to mitigate the impacts of high river temperatures.