Drivers of interannual and intra‐annual variability of dissolved organic carbon concentration in the River Thames between 1884 and 2013

The world's longest record of river water quality (River Thames—130 years) provides a unique opportunity to understand fluvial dissolved organic carbon (DOC) concentrations dynamics. Understanding riverine DOC variability through long‐term studies is crucial to capture patterns and drivers influencing sources of DOC at scales relevant for decision making. The Thames basin (United Kingdom) has undergone massive land‐use change, as well as increased urbanisation and population during the period considered. We aimed to investigate the drivers of intra‐annual to interannual DOC variability, assess the variability due to natural and anthropogenic factors, and understand the causes for the increased DOC variability over the period. Two approaches were used to achieve these aims. The first method was singular spectrum analysis, which was used to reconstruct the major oscillatory modes of DOC, hydroclimatic variables, and atmospheric circulation patterns and to visualise the interaction between these variables. The second approach used was generalised additive modelling, which was used to investigate other non‐natural drivers of DOC variability. Our study shows that DOC variability increased by 80% over the data period, with the greatest increase occurring from the beginning of World War II onwards. The primary driver of the increase in DOC variability was the increase in the average value of fluvial DOC over the period of record, which was itself linked to the increase in basin population and diffuse DOC sources to the river due to land‐use and land‐management changes. Seasonal DOC variability was linked to streamflow and temperature. Our study allows to identify drivers of fluvial intra‐annual and interannual DOC variability and therefore empowers actions to reduce high DOC concentrations.     

Artificial neural network modelling of concentrations of nitrogen,phosphorus and dissolved oxygen in a non‐point source polluted river in Zhejiang Province,southeast China

A back‐propagation algorithm neural network (BPNN) was developed to synchronously simulate concentrations of total nitrogen (TN), total phosphorus (TP) and dissolved oxygen (DO) in response to agricultural non‐point source pollution (AGNPS) for any month and location in the Changle River, southeast China. Monthly river flow, water temperature, flow travel time, rainfall and upstream TN, TP and DO concentrations were selected as initial inputs of the BPNN through coupling correlation analysis and quadratic polynomial stepwise regression analysis for the outputs, i.e. downstream TN, TP and DO concentrations. The input variables and number of hidden nodes of the BPNN were then optimized using a combination of growing and pruning methods. The final structure of the BPNN was determined from simulated data based on experimental data for both the training and validation phases. The predicted values obtained using a BPNN consisting of the seven initial input variables (described above), one hidden layer with four nodes and three output variables matched well with observed values. The model indicated that decreasing upstream input concentrations during the dry season and control of NPS along the reach during average and flood seasons may be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data are available, the methodology developed here can easily be applied to other case studies. The BPNN model is an easy‐to‐use modelling tool for managers to obtain rapid preliminary identification of spatiotemporal water quality variations in response to natural and artificial modifications of an agricultural drainage river. Copyright © 2009 John Wiley & Sons, Ltd.     

Monitoring and modeling dissolved oxygen dynamics through continuous longitudinal sampling: a case study in Wen‐Rui Tang River,Wenzhou, China

Synoptic water sampling at a fixed site monitoring station provides only limited ‘snap‐shots’ of the complex water quality dynamics within a surface water system. However, water quality often changes rapidly in both spatial and temporal dimensions, especially in highly polluted urban rivers. In this study, we designed and applied a continuous longitudinal sampling technique to monitor the fine‐scale spatial changes of water quality conditions, assess water pollutant sources, and determine the assimilative capacity for biochemical oxygen demand (BOD) in an urban segment of the hypoxic Wen‐Rui Tang River in eastern China. The continuous longitudinal sampling was capable of collecting dissolved oxygen (DO) data every 5 s yielding a ~11 m sampling interval with a precision of ±0.1 mg L^?1. The Streeter and Phelps BOD‐DO model was used to calculate: (1) the oxygen consumption coefficient (K₁) required for calibration of water quality models, (2) BOD assimilative capacity, and (3) BOD source and load identification. In the 2014 m river segment sampled, the oxygen consumption coefficient (K₁) was 0.428 d^?1 (20°C), the total BOD discharge was 916 kg d^?1, and the BOD assimilative capacity was 382 kg d^?1 when the minimum DO level was set to 2 mg L^?1. In addition, the longitudinal analysis identified eight major drainage outlets (BOD point sources), which were verified by field observations. This new approach provides a simple, cost‐effective method of evaluating BOD‐DO dynamics over large spatial areas with rapidly changing water quality conditions, such as urban environments. It represents a major breakthrough in the development and application of water quality sampling techniques to obtain spatially distributed DO and BOD in real time. Copyright © 2012 John Wiley & Sons, Ltd.     

A comparison of groundwater recharge estimation methods in a semi‐arid,coastal avocado and citrus orchard (Ventura County,California)

We assess the relative merits of application of the most commonly used field methods (soil‐water balance (SWB), chloride mass balance (CMB) and soil moisture monitoring (NP)) to determine recharge rates in micro‐irrigated and non‐irrigated areas of a semi‐arid coastal orchard located in a relatively complex geological environment. Application of the CMB method to estimate recharge rates was difficult owing to the unusually high, variable soil‐water chloride concentrations. In addition, contrary to that expected, the chloride concentration distribution at depths below the root zone in the non‐irrigated soil profiles was greater than that in the irrigated profiles. The CMB method severely underestimated recharge rates in the non‐irrigated areas when compared with the other methods, although the CMB method estimated recharge rates for the irrigated areas, that were similar to those from the other methods, ranging from 42 to 141 mm/year. The SWB method, constructed for a 15‐year period, provided insight into the recharge process being driven by winter rains rather than summer irrigation and indicated an average rate of 75 mm/year and 164 mm/year for the 1984 – 98 and 1996 – 98 periods, respectively. Assuming similar soil‐water holding capacity, these recharge rates applied to both irrigated and non‐irrigated areas. Use of the long period of record was important because it encompassed both drought and heavy rainfall years. Successful application of the SWB method, however, required considerable additional field measurements of orchard ET_c, soil‐water holding capacity and estimation of rainfall interception – runoff losses. Continuous soil moisture monitoring (NP) was necessary to identify both daily and seasonal seepage processes to corroborate the other recharge estimates. Measured recharge rates during the 1996 – 1998 period in both the orchards and non‐irrigated site averaged 180 mm/year. The pattern of soil profile drying during the summer irrigation season, followed by progressive wetting during the winter rainy season was observed in both irrigated and non‐irrigated soil profiles, confirming that groundwater recharge was rainfall driven and that micro‐irrigation did not ‘predispose’ the soil profile to excess rainfall recharge. The ability to make this recharge assessment, however, depended on making multiple field measurements associated with all three methods, suggesting that any one should not be used alone. Copyright © 2000 John Wiley & Sons, Ltd.     

Inter‐annual variability in the effects of riparian woodland on micro‐climate,energy exchanges and water temperature of an upland Scottish stream

The influence of riparian woodland on stream temperature, micro‐climate and energy exchange was investigated over seven calendar years. Continuous data were collected from two reaches of the Girnock Burn (a tributary of the Aberdeenshire Dee, Scotland) with contrasting land use characteristics: (1) semi‐natural riparian forest and (2) open moorland. In the moorland reach, wind speed and energy fluxes (especially net radiation, latent heat and sensible heat) varied considerably between years because of variable riparian micro‐climate coupled strongly to prevailing meteorological conditions. In the forested reach, riparian vegetation sheltered the stream from meteorological conditions that produced a moderated micro‐climate and thus energy exchange conditions, which were relatively stable between years. Net energy gains (losses) in spring and summer (autumn and winter) were typically greater in the moorland than the forest. However, when particularly high latent heat loss or low net radiation gain occurred in the moorland, net energy gain (loss) was less than that in the forest during the spring and summer (autumn and winter) months. Spring and summer water temperature was typically cooler in the forest and characterised by less inter‐annual variability due to reduced, more inter‐annually stable energy gain in the forested reach. The effect of riparian vegetation on autumn and winter water temperature dynamics was less clear because of the confounding effects of reach‐scale inflows of thermally stable groundwater in the moorland reach, which strongly influenced the local heat budget. These findings provide new insights as to the hydrometeorological conditions under which semi‐natural riparian forest may be effective in mitigating river thermal variability, notably peaks, under present and future climates. © 2014 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.     

Detecting the flow relationships between deep and shallow aquifers in an exploited groundwater system,using long‐term monitoring data and quantitative hydrogeology: the Acque Albule basin case (Rome,Italy)

Five years of hydrogeological monitoring and field activities performed in the complex hydrogeological system of the Acque Albule basin (AAB) were conducted to define the hydrogeological setting, the relationship between deep and shallow aquifers and a conceptual groundwater flow model of this exploited area using conventional quantitative techniques. The basin, which is located close to Rome (Italy) on the west side of the Apennine chain and just north of the Colli Albani volcano, subsided after development of a north–south fault system (about 115 000 y bp). The AAB experiences intense hydrothermal activity, which has produced a large travertine deposit (80‐m thick). The travertine deposit constitutes a fractured aquifer that is the final destination of more than 5 m³ s^‐1 of water and is strongly dewatered by quarry activities. The complex hydrogeology of this basin was investigated, revealing two main hydraulically connected aquifers, one thermalised and partly confined into the limestone bedrock and one unconfined in the travertine. The two aquifers are separated by a non‐continuous clayey aquiclude. The hydrogeological survey and geological characterisation contributed to the development of the groundwater flow conceptual model. Analysis and comparison of the monitored levels highlighted the pattern of flow between the deep and shallow parts of the flow system. Copyright © 2012 John Wiley & Sons, Ltd.