The artificial recharge of groundwater: A solution by successive variations of steady states

The artificial recharge of groundwater aims at the modification of water quality, an increase of groundwater resources, and the optimization of the exploitation and recovery of contaminated aquifers. The purpose of this work is to develop a new mathematical model for the problem of an artificial recharge well, using the method of successive variations of steady states. Applying this method, one arrives at an expression of time as a double integral. This integral contains the time-dependent radius of the recharge boundary and the piezometric head of the well, calculated with the finite-element method. The new model is simple and useful, and can be applied to many practical problems, using the designed dimensionless graphs.Notations A area of the finite element (m²) - c the Euler constant (0.5772156649...) - e index of the finite element - E _i the exponential integral function - F _j nodal values of the functionF - h piezometric head, (m) - h ₀ piezometric head at timet=0 (m) - h _w piezometric head on the well contour (m) - i, j, k nodal indices of the finite element - K hydraulic contactivity (ms^–1) - N _i interpolation function - Q discharge (m³ s^–1) - r cylindrical coordinate (m) - r ₀ the action radius of the well (m) - r _w the radius of the well (m) - S the effective porosity - t the time (s) - T the transmissivity of the aquifer (m²s^–1) - V the stored water volume (m³) - x, y, dummy variables     

Combined analytical solution of overland flow and sediment transport

With reference to the kinematic wave theory coupled with the hypothesis of constant linear velocity for the rating curve, rising limb analytical solutions have been calculated for overland flow, over an Hortonian-infiltrating surface, and sediment discharge. These analytical solutions are certainly easier to use than the numerical integration of the basic equations and they may be used to obtain an initial evaluation of the parameters of more complex models generally devised for complicated cases.Notation a exponent of the Horton law [T^–1] - b exponent of the rill erosion equation - B inter-rill erosion coefficient [ML^–m–2T ^m–1] - c sediment concentration [ML^–3] - c _o reference sediment concentration [ML^–3] - E _I inter-rill erosion [ML^–2T^–1] - E _R rill erosion [ML^–2T^–1] - f _c final infiltration rate of the soil [LT^–1] - f _o initial infiltration rate of the soil [LT^–1] - h flow depth [L] - h _o reference flow depth [L] - i infiltration rate [LT^–1] - k rill erosion coefficient [ML^–1–b T^–1] - K integration constant - L() Laplace transformation - m exponent of the inter-rill erosion equation - n Manning's coefficient [L^–1/3T] - p rainfall intensity [LT^–1] - q water discharge per unit width [L²T^–1] - q _s sediment discharge per unit width [ML^–1T^–1] - t time [T] - t _p ponding time [T] - x distance along the flow direction [L] Greek Letters coefficient of the stage-discharge equation [L^2–T^–1] - exponent of the stage-discharge equation - rill erosion coefficient [L^–1]     

An application of linear programming to determine optimal systems for rainwater management: An economic view

Two decision models, one for determining optimal systems for rainwater management and the other for allocating additional water supplies from managed rainfall in conjunction with irrigation water, are formulated. The application of a rainwater management model to the command and to a watercourse, decides the minimum cost activities to manage rainwater. The output from the first model is used as the input in the second model which optimally allocates water to competing crops. It has been shown that 80% of rainwater could be managed economically in rice fields and in storage underground through artificial recharge. Optimal allocation of managed rainwater in conjunction with irrigation water increases the income of the project area to the extent of 14%.List of symbols AER Total available energy kWh - B _max Maximized value of the objective function, Rs - C _W Cost of canal water, Rs/10³ m³ - C _i Cost of managing rainwater through activityi, Rs/10³/m³ - C _min Minimized cost of managing surplus rainwater, Rs - C _RF Average cost of managed rainwater through activityi, Rs/10³ m³ - E _i Energy consumption in rainwater management activityi, kWh/10³ m³ (only energy required for pumping water is considered) - FLS Available capacity for fallow land storage, 10³ m³ - FPS Total storage in lined and unlined farm ponds, 10³ m³ - GWR Runoff diversion for artificial recharge through inverted tubewells, 10³ m³ - i A suffix for management activities having values 1,2,3,..., - j Crop index having values 1,2,3,..., - k Index for crop season, 1=kharif (summer) and 2=rabi(winter) - MRF Maximum rainfall surplus (runoff) available for management. (Runoff value at a 5-year return period was adopted) - P _j Income from crop activityj, Rs/ha - RFL Storage in fallow alkali land, 10³ m³ - RFS Storage in rice fields up to various depths, 10³ m³ - RWM _i Volume of rainwater managed through activityi, 10³ m³ - VCW Volume of canal water, 10³ m³ - VGW Volume of ground water, 10³ m³ - X _j Area under cropj, ha.     

Analytical solutions of unsteady drainage problems for soils subjected to variable recharge from a semi-confined aquifer

In drainage of agricultural lands, the upward vertical recharge from a semi-confined aquifer depends on the difference of the piezometric heads on the two sides of the semi-impermeable layer through which this recharge takes place. This means that the recharge through the semi-impermeable base depends on the unknown height of the unsteady water table. In the nonhomogeneous Boussinesq equation, which describes the drainage problems, the downward uniform rate of the recharge from rain or irrigation and the recharge from the semiconfined aquifer are expressed by two terms. By solving the Boussinesq equation expressions for the nondimensional height of the water table and the nondimensional discharge of the drains per unit drained area are obtained for three different initial conditions. Some known solutions are shown as special cases of the present solutions. Variation of nondimensional water table heights at half distance of the drain spacing and the nondimensional discharge of the drains with nondimensional time have been graphically illustrated with the help of synthetic examples.Notation B _s thickness of the semi-impervious layer [L] - c hydraulic resistance of the semi-impervious layer [T] - D depth of the drains from the base [L] - d _e equivalent depth [L] - h=h(x, t) height of the water table [L] - h ₀ initial height of the water table [L] - h _t water table height at mid-distance of drains att [L] - h _j ,h _k water table height at mid-distance of drains at timej andfk, respectively [L] - H ₀ piezometric head in the semi-confined aquifer [L] - K hydraulic conductivity of the soil [LT^–1] - K _s hydraulic conductivity of the semi-impervious layer [LT^–1] - k ₀,k ₁,k ₂ nondimensional constants - L distance between the drains [L] - q ₀ upward recharge per unit surface area through the semi-impervious layer [LT^–1] - q _t discharge per unit drainable area of drains at timet [LT^–1] - R,R ₀ recharge per unit surface area from rain or irrigation during the unsteady and steady-state, respectively, [LT^–1] - S specific yield of the soil - t time of observation [T] - x distance measured from the drain [L] - leakage factor [L] - nondimensional distance - nondimensional time     

Water table fluctuation due to transient recharge in a 2-D aquifer system with inclined base

Recharging of aquifers due to irrigation, seepage from canal beds and other sources leads to the growth of water table near to the ground surface causing problems like water logging and increase of salinity in top soils in many regions of the world. This problem can be alleviated if proper knowledge of the spatio — temporal variation of the water table is available. In this paper an analytical solution for the water table fluctuation is presented for a 2-D aquifer system having inclined impervious base with a small slope in one — direction and receiving time varying vertical recharge. Application of the solution in estimation of water table fluctuation is demonstrated with the help of an example problem.Notations A length of the aquifer [L] - B width of the aquifer [L] - D mean depth of saturation [L] - e specific yields - h variable water table height [L] - K hydraulic conductivity [LT ^–1] - P(t) transient recharge rate [LT ^–1] - P ₁+P _o initial rate of transient recharge [LT ^–1] - P ₁ final rate of transient recharge [LT ^–1] - q slope of the aquifer base in percentage - r decay constant [T ^–1] - t time of observation [T] - x, y coordinate axes - x ₂–x ₁ length of the recharge basin [L] - y ₂–y ₁ width of the recharge basin [L]     

Modelling Temperature,Body Size,Prey Density,and Stream Gradient Impacts on Longitudinal Patterns of Potential Production of Drift‐Feeding Trout

In this study, we modelled idealized stream reaches using empirical hydrodynamic and bioenergetic parameters to predict how rainbow trout production depends on physical and biological variations across a downstream gradient, and we compared these downstream effects in a low and high‐gradient stream reach. We found that longitudinal production potential (i.e. net rate of energetic intake per 100 m of stream length) generally increased with increasing stream size when stream gradient was low. This was not the case, however, for high‐gradient streams, wherein maximum longitudinal production potential was associated with middle or low stream size (Q_MAD = 2.5 to 25 m³ s^?1). Areal production potential (net rate of energetic intake per m² of wetted stream bed) reached a maximum at low stream size (Q_MAD = 2.5 m³ s^?1) with both high and low gradients. We also showed that high stream temperature and low drift density could potentially cause adult rainbow trout to be excluded from stream reaches with high flow. The models presented here have a stronger mechanistic basis for predicting fish production across heterogeneous stream environments and provide more nuanced predictions in response to variation in environmental features than their physical habitat‐based predecessors. Copyright © 2016 John Wiley & Sons, Ltd.     

An analytical solution for water-table fluctuation in a finite aquifer due to transient recharge from a strip basin

Two cases of water-table fluctuation in a finite aquifer in response to transient recharge from a strip basin are investigated. In the first case the aquifer is bounded by open water-bodies, whereas in second one the aquifer is bounded by impermeable boundaries on both sides. Analytical solutions are presented to predict the transient position of the water-table. The solutions are obtained by using finite Fourier sine and cosine transforms.Notations A width of the aquifer [L] - e specific yield - h variable water-table height [L] - h ₀ initial water-table height [L] - weighted mean of the depth of saturation [L] - K hydraulic conductivity [LT^–1] - m,n integers - P ₁ +P ₀ initial rate of transient recharge [LT^–1] - P ₁ final rate of transient recharge [LT^–1] - P constant rate of recharge [LT^–1] - x ₁ distance of left boundary of the strip basin [L] - x ₂ distance of right boundary of the strip basin [L] - t time of observation [T] - decay constant [T^–1]     

Determination of optimal unit hydrographs by linear programming

A unit hydrograph (UH) obtained from past storms can be used to predict a direct runoff hydrograph (DRH) based on the effective rainfall hyetograph (ERH) of a new storm. The objective functions in commonly used linear programming (LP) formulations for obtaining an optimal UH are (1) minimizing the sum of absolute deviations (MSAD) and (2) minimizing the largest absolute deviation (MLAD). This paper proposes two alternative LP formulations for obtaining an optimal UH, namely, (1) minimizing the weighted sum of absolute deviations (MWSAD) and (2) minimizing the range of deviations (MRNG). In this paper the predicted DRHs as well as the regenerated DRHs by using the UHs obtained from different LP formulations were compared using a statistical cross-validation technique. The golden section search method was used to determine the optimal weights for the model of MWSAD. The numerical results show that the UH by MRNG is better than that by MLAD in regenerating and predicting DRHs. It is also found that the model MWSAD with a properly selected weighing function would produce a UH that is better in predicting the DRHs than the commonly used MSAD.Notations M number of effective rainfall increments - N number of direct runoff hydrograph ordinates - R number of storms - MSAD minimize sum of absolute deviation - MWSAD minimize weighted sum of absolute deviation - MLAD minimize the largest absolute deviation - MRNG minimize the range of deviation - RMSE root mean square error - P _m effective rainfall in time interval [(m–1)t,mt] - Q _n direct runoff at discrete timent - U _k unit hydrograph ordinate at discrete timekt - W _n weight assigned to error associated with estimatingQ _n - _n ⁺ error associated with over-estimation ofQ _n - _n ^– error associated with under-estimation ofQ _n - _max ⁺ maximum positive error in fitting direct runoff hydrograph - _max ^– maximum negative error in fitting direct runoff hydrograph - _max largest absolute error in fitting obtained direct runoff - E _r,1 thelth error criterion measuring the fit between the observed DRHs and the predicted (or reproduced) DRHs for therth storm - E ₁ averaged value of error criterion overR storms     

On the prediction of groundwater mound formation due to transient recharge from a rectangular area

Recharge to the aquifer leads to the growth of a groundwater mound. Therefore, for the proper management of an aquifer system, an accurate prediction of the spatio-temporal variation of the water table is very essential. In this paper, a problem of groundwater mound formation in response to a transient recharge from a rectangular area is investigated. An approximate analytical solution has been developed to predict the transient evolution of the water table. Application of the solution and its sensitivity to the variation of the recharge rate have been illustrated with the help of a numerical example.Notations a = Kh/e [L²/T] - A = aquifer's extent in the x-direction [L] - B = aquifer's extent in the y-direction [L] - e = effective porosity - h = variable water table height [L] - h ₀= initial water table height [L] - h = weighted mean of the depth of saturation [L] - K = hydraulic conductivity [L] - m, n = integers - P = constant rate of recharge [L/T] - P ₁+P₀= initial rate of transient recharge [L/T] - P ₁= final rate of transient recharge [L/T] - s = h ²–h ₀ ² [L²] - t = time of observation [T] - x,y = space coordinates - x ₂–x₁= length of recharge area in x-direction [L] - y ₂–y₁= width of recharge area in y-direction [L] - z = decay constant [T^-1]     

Water table fluctuation in response to transient recharge from a rectangular basin

A problem of water-table fluctuation in a finite two-dimensional aquifer system in response to transient recharge from an overlying rectangular area is studied. An analytical solution is obtained by using the method of finite Fourier transform to predict the transient position of the water-table. The solution for constant rate of recharge is shown as a special case of the present solution. Effects of variation in the rate of recharge on the growth of two-dimensional groundwater mound is illustrated with the help of a numerical example.Notation A half width of the aquifer [L] - B half length of the aquifer [L] - D half width of the recharge basin [L] - e specific yield - h varying water-table height [L] - h ₀ initial water-table height [L] - h weighted mean of the depth of saturation [L] - K hydraulic conductivity [LT^–1] - L half length of the recharge basin [L] - P(t) time varying rate of recharge [LT^–1] - P ₁ +P ₀ initial rate of time varying recharge [LT^–1] - P ₁ final rate of time varying recharge [LT^–1] - t time of observation [T] - x, y coordinate axes - decay constant [T^–1]     

Optimization-simulation models for the design of an Irrigation project

Optimization-simulation models were used for the systems analysis of a water resources system. The Karjan Irrigation reservoir project in India was taken as the system. Two types of optimization models, i.e., linear programming, and dynamic programming (continuous and discontinuous) were used for preliminary design purposes. The simulation technique was used for further screening. The linear programming model is most suitable for finding reservoir capacity. Dynamic programming (continuous and discontinuous models) may be used for further refining the output targets and finding the possible reservoir carry-over storages, respectively. The simulation should then be used to obtain the near optimum values of the design variables.Notations a ₁ Unit irrigation benefit [Rs.10⁵ L^–3] - B ₁ Gross annual irrigation benefit [Rs.10⁵] - B _1,t Gross irrigation benefit in periodt [Rs.10⁵] - C ₁ Annual capital cost of irrigation [Rs.10⁵] - C ₁ Annual capital cost function for irrigation [Rs.10⁵ L^–3] - C _1,t Fraction of annual capital cost for irrigation in periodt [Rs.10⁵] - C ₂ Annual capital cost of reservoir [Rs.10⁵] - C ₂ Annual capital cost function for reservoir [Rs.10⁵ L^–3] - C _2,t Fraction of annual capital cost for reservoir in periodt [Rs.10⁵] - El _t Reservoir evaporation in timet [L³] - f _t Optimal return from staget [Rs.10⁵] - g _t The return function for periodt [Rs.10⁵] - I _t Catchment inflow into the reservoir in periodt [L³] - I _t Water that joins the main stem just above the irrigation diversion canal in timet [L³] - _t Local inflow to the reservoir from the surrounding area in timet [L³] - Ir Annual irrigation target [L³] - K _t Proportion of annual irrigation targetIr to be diverted for irrigation in timet - K _t Amount by whichK _t exceeds unity is the fraction of the end storage which is assigned to reservoir evaporation losses - L Loss in irrigation benefits per unit deficit in the supply [Rs.10⁵ L^–3] - L ₁ Lower bound on annual irrigation target,Ir [L³] - L ₂ Lower bound on reservoir capacity,Y [L³] - N Number of time periods in the planning horizon - O _t Total water release from the reservoir in periodt [L³] - O _t ^* The optimal total water release from the reservoir in timet [L³] - _t Secondary water release from the reservoir in timet [L³] - O _t Reservoir release to the natural channel in timet [L³] - Od _t Irrigation demand in timet [L³] - Om ₁ Annual OM cost of irrigation [Rs.10⁵] - Om ₁ Annual OM cost function for irrigation [Rs.10⁵ L^–3] - Om _1,t Fraction of annual OM cost for irrigation in periodt [Rs.10⁵] - Om ₂ Annual OM cost of reservoir [Rs.10⁵] - Om ₂ Annual OM cost function for reservoir [Rs.10⁵ L^–3] - Om _2,t Fraction of annual OM cost for reservoir in periodt [L³] - Omin_t Lower bound onO _t in timet [L³] - Omax_t Upper bound onO _t in timet [L³] - P _t Precipitation directly upon reservoir in timet [L³] - S _t Gross/live reservoir storage at the end of timet (gross storage in the linear program and live storage in the dynamic program) [L³] - S _t–1 Gross/live reservoir storage at the beginning of timet [L³] - t Any time period - Tr_t Transformation function - U ₁ Upper bound onIr [L³] - U ₂ Upper bound onY [L³] - Y Total capacity of reservoir at maximum pool level [L³] - Ya Fixed active (live) capacity of the reservoir (Y-Yd) [L³] - Ya _t Active (live) capacity (Ymax_t –Ymin_t) of the reservoir in timet [L³] - Yd Dead storage of the reservoir [L³] - Ymax_t Capacity up to the normal pool level of the reservoir in timet [L³] - Ymax_t Live capacity up to the normal pool level of the reservoir in timet [L³] - Ymin_t Capacity up to the minimum pool level of the reservoir in timet [L³] - Ymin_t Live capacity up to the minimum pool level of the reservoir in timet [L³]     

Design of a bilateral-symmetric multi-slot fishway and its comparison with vertical slot fishway in terms of hydraulic properties

Aiming at improving the hydraulic properties and enhancing the fish passage efficiency, this study proposes a novel bilateral-symmetric multi-slot fishway (BMSF) by combining the structural features of a double-sided vertical-slot fishway, multi-slot fishway and T-shape fishway. Eight BMSF cases are further designed by adjusting the slot width and the distance between the short baffle and the front end of the central wall, in order to achieve the relatively best hydrodynamic characteristics. The flow fields of two vertical-slot fishways and eight BMSF fishways are obtained by numerically solving the Reynolds-averaged Navier–Stokes equation, the volume-of-fluid equation and the k-ω-SST turbulence model. Numerical results manifest that the recommended BMSF-8 provides the smallest values in terms of the maximum time-averaged velocity magnitude (1.42 m s⁻¹), the maximum time-averaged turbulent kinetic energy (0.132 m² s⁻²), the maximum time-averaged Reynolds shear stress component (44 Pa), the spatial-mean time-averaged velocity magnitude (0.58 m s⁻¹), and the spatial-mean time-averaged turbulent kinetic energy (0.042 m² s⁻²) in the middle pool at Q = 1000 L/s. Even for the depth-mean time-averaged velocity magnitude at the slot and the volume percentages of some critical physical quantities, BMSF-8 is also superior to the other cases. To sum up, BMSF-8 leads to the relatively lowest flow velocity and turbulence, being more suitable for the passage of the whole fish community (especially for small-sized fishes with weaker swimming ability). In addition, the generalizability of the aforementioned superiority of BMSF-8 is displayed by providing the numerical results of four operating conditions (i.e., Q = 600, 800, 1000 and 1200 L/s).     

Development of Regional Flood Frequency Relationships Using L-moments for Middle Ganga Plains Subzone 1(f) of India

In this study, screening of the data has been carried out basedon the discordancy measure (D _i) in terms of the L-moments. Homogeneity of the region has been tested using the L-moments based heterogeneity measure, H. For computing the heterogeneity measure H, 500 simulations were carried out using the four parameter Kappa distribution. Based on this test, it has been observed that the data of 8 out of 11 bridge sites constitute ahomogeneous region. Hence, the data of these 8 sites have been used in this study. Catchment areas of these 8 sites vary from 32.89 to 447.76 km² and their mean annual peak floods varyfrom 24.29 to 555.21 m³ s^-1. Comparative regional floodfrequency analysis studies have been carried out using the various L-moments based frequency distributions viz. Extreme value (EV1), General extreme value (GEV), Logistic (LOS), Generalized logistic (GLO), Normal (NOR), Generalized normal (GNO), Uniform (UNF), Pearson Type-III (PE3), Exponential (EXP),Generalized Pareto (GPA), Kappa (KAP), and five parameter Wakeby(WAK). Based on the L-moment ratio diagram and Z _i ^dist –statistic criteria, GEV distribution has been identified as the robust distribution for the study area. For estimation of floods of various return periods for gauged catchments of the study area, regional flood frequency relationship has been developed using the L-moments based GEV distribution. Also, for estimation of floods of desiredreturn periods for ungauged catchments, regional flood frequencyrelationship has been developed by coupling the regional flood frequency relationship with the regional relationship between mean annual maximum peak flood and catchment area.     

Forecast model of water consumption for Naples

The data refer to the monthly water consumption in the Neapolitan area over more than a 30 year period. The model proposed makes it possible to separate the trend in the water consumption time series from the seasonal fluctuation characterized by monthly peak coefficients with residual component. An ARMA (1,1) model has been used to fit the residual component process. Furthermore, the availability of daily water consumption data for a three-year period allows the calculation of the daily peak coefficients for each month, and makes it possible to determine future water demand on the day of peak water consumption.Notation j numerical order of the month in the year - i numerical order of the year in the time series - t numerical order of the month in the time series - h numerical order of the month in the sequence of measured and predicted consumption values after the final stage t of the observation period - Z _ji effective monthly water consumption in the month j in the year i (expressed as m³/day) - T _ji predicted monthly water consumption in the month j in the year i minus the seasonal and stochastic component (expressed as m³/day) - C _ji monthly peak coefficient - E _ji stochastic component of the monthly water consumption in the month of j in the year i - Z _i water consumption in the year i (expressed as m³/year) - Z _j (t) water consumption in the month j during the observation period (expressed as m³/day) - evaluation of the correlation coefficient - Z _j (t) water consumption in the month j during the observation period minus the trend - Y _t transformed stochastic component from E _t : Y _t =ln Et - Y _t+h measured value of stochastic component for t+h period after the final stage t of the observation period - Y _t (h) predicted value of stochastic component for t+h period after the final stage t of the observation period - _j transformation coefficients from the ARMA process (m, n) to the MA () process     

THE SOLAR‐TO‐STREAM POWER RATIO: A DIMENSIONLESS NUMBER EXPLAINING DIEL FLUCTUATIONS OF TEMPERATURE IN MESOSCALE RIVERS

The diel variation of temperature in mesoscale river reaches (catchment area > 1000 km²) is analysed using concurrent measurements of water temperature and of those meteorological (incident short‐wave radiation, air temperature, relative humidity and wind speed variables) and hydraulic variables (streamflow, top width, channel slope and flow depth) controlling the thermal regime. Measurements were taken along two river reaches located in central Chile, on the Itata (11 290 km², Strahler's order 6, reach length 30 km, Q_bankfull = 400 m³ s^?1) and Vergara (4340 km², Strahler's order 5, reach length 20 km, Q_bankfull = 85 m³ s^?1) rivers. The measuring frequency was 15 min. The relevant energy fluxes at the air–water interface, that is, atmospheric long‐wave radiation, net short‐wave radiation, radiation emitted by the water body, evaporation (latent heat) and conduction heat are computed and analysed for four scenarios of 12 days duration each, representing typical conditions for the austral winter, spring, summer and autumn. We find large differences in the diel river temperature range between the two sites and across seasons (and thus, flows and meteorological conditions), as reported in previous studies, but no clear relationship with the controlling variables is overtly observed. Following a dimensional analysis, we obtain a dimensionless parameter corresponding to the ratio of solar‐to‐stream power, which adequately explains the diel variation of water temperature in mesoscale rivers. A number of our own measurements as well as literature data are used for preliminary testing of the proposed parameter. This easy‐to‐compute number is shown to predict quite well all of the cases, constituting a simple and useful criterion to estimate a priori the magnitude of temperature diel variations in a river reach, given prevailing meteorological (daily maximum solar radiation) and hydrologic–hydraulic (streamflow, mean top width) conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Nitrogen processing by biofilms along a lowland river continuum

While numerous studies have examined N dynamics along a river continuum, few have specifically examined the role of biofilms. Nitrogen dynamics and microbial community structure were determined on biofilms at six sites along a 120 km stretch of the lowland Ovens River, South Eastern Australia using artificial substrates. Terminal restriction fragment length polymorphism (T‐RFLP), chlorophyll a and protein analyses were used to assess biofilm microbial community composition. N dynamics was determined on the biofilms using the acetylene (C₂H₂) block technique and assessing changes in NH, NO_x and N₂O. Unlike microbial community structure, N dynamics were spatially heterogeneous. Nitrification, determined from the difference in accumulation of NH before and after addition of C₂H₂, occurred mostly in the upper sites with rates up to 1.4 × 10^?5 mol m^?2 h^?1. The highest rates of denitrification occurred in the mid‐reaches of the river (with rates up to 1 × 10^?5 mol m^?2 h^?1) but denitrification was not detected in the lower reaches. At the very most, only 50% of the observed uptake of NO_x by the biofilms following addition of C₂H₂ could be accounted for by denitrification. Copyright © 2005 John Wiley & Sons, Ltd.     

Merging anchovy eggs abundance into a hydrodynamic model as an assessment tool for estuarine ecohydrological management

The impoundment of rivers by large dams is the biggest direct anthropogenic impact on the hydrological cycle. However, dams can help solving eutrophication in estuaries by controlling flow pulses, which in turn might enhance the advection of fish larval stages from their spawning and nursery areas. Thus, this work aimed to merge data on the abundance of anchovy eggs with MOHID hydrodynamic model for the Guadiana estuary, allowing dam/basin managers to set river discharge scenarios that might mitigate/prevent eutrophication, without compromising the presence of fish larval stages inside the estuary. Data on anchovy larval stages were assessed in the Guadiana estuary and adjacent coast and three simulation setups were developed. In Simulation A, anchovy eggs abundance was merged in the hydrodynamic model to compare the outputs with data on the abundance, distribution and development stage of anchovy eggs and larvae. In Simulation B, lagrangian particles were incorporated in the model to determine the percentage of particles released from the upper, middle and lower estuary that remain in the estuary along 10 days, in two tidal situations and in seven river discharge scenarios. In Simulation C, the abundance of anchovy eggs was merged in the model to select the discharge scenario(s) that do not compromise the presence of anchovy larval stages in the estuary. Results confirmed the spawning and nursery areas of anchovy and showed that scenarios B (Q_max = 20 m³ s^?1) and C (Q_max = 50 m³ s^?1) should be applied during neap tides. The choice between scenarios depends on the degree of eutrophication, the effectiveness of an inexistent monitoring program and on plankton response experiments to flushing and increased nutrient loading. This work produced an easy‐to‐use management tool for Guadiana managers, serving as an example to other estuarine sites around the world. Ultimately, this work suggests that river flow management must be guided by robust ecological studies, under an adequate sociological framework and adopting sustainable economic principles to maintain and improve the ecosystem services. Copyright © 2010 John Wiley & Sons, Ltd.     

A comparison of methods for evaluating instream flow needs for recreation along rivers in southern Alberta,Canada

Four methods were compared for determining recreational instream flow needs (R‐IFN) for paddling canoes, kayaks and rafts on ten river reaches in the Oldman River Basin of southern Alberta. Two flow criteria were evaluated: ‘minimal flow’—the low flow that still provides a reasonable quality river trip; and ‘sufficient flow’—the lower end of the favoured flow range. A voluntary, mail‐in user survey from 1983 to 1997 produced 394 responses (4251 paddler days) relative to flow suitability. An expert judgment approach considered flow recommendations from three regional paddling guides that were considered comprehensive and credible. A flow comparison involved about 20 paddle trips per reach by the authors with differing groups, boats and flows. These subjective approaches produced quite consistent results (r² = 0.63) and these were compared to results from an objective, hydraulic modelling method, the ‘depth, discharge method’ (DDM), that applied stage–discharge functions to determine flows that would satisfy depth criteria of 60 and 75 cm. The DDM minimal flows were closely correlated with the means of the subjective methods (r² = 0.73). Thus, all four approaches produced generally consistent results, indicating that all methods were valid. Typical minimal and sufficient flows were about 15 and 30 m³ s^?1, respectively, for the medium‐sized river reaches that had average annual discharges (mean Q) of about 20 m³ s^?1. A close correlation (r² = 0.90) between the minimal flow and mean Q suggests that mean Q can provide an initial estimate for R‐IFN for rivers of this type and size. We recommend that R‐IFN studies commence with the DDM since it is quick, inexpensive and objectively defensible. This would provide guidelines for subsequent subjective assessments that should involve more than one approach to increase the breadth of subjective consideration. Copyright © 2003 John Wiley & Sons, Ltd.     

Instream flows for recreation are closely correlated with mean discharge for rivers of western North America

Effective river regulation requires consideration for environmental and economic aspects and also for social aspects including recreation. Our study investigated relationships between river hydrology and recreational flows (RF) for canoes, kayaks, rafts and other non‐motorized boats, for 27 river reaches in the Red Deer and Bow river basins of southern Alberta, Canada. A subjective RF method involved regression analyses of data from River Trip Report Cards, volunteer postcard‐style surveys rating flow sufficiency. A total of 958 trip reports were submitted for the rivers between 1983 and 1997 and about 30 reports permitted confident regression analysis for a river reach. Values from these analyses were very consistent with values from the ‘depth discharge method’, a hydraulic modelling approach that used stage–discharge ratings to determine flows that would produce typical depths of 60 and 75 cm for minimal and preferred flows, respectively. Values were also consistent with expert opinions from river guidebooks and maps and aggregate values were calculated from the combined RF methods. These were very closely correlated with mean discharge (Q_m) across the rivers (r² = 0.94 for minimal and 0.96 for preferred flows). The relationship best fitted a power function (straight plot on log versus log scales) with a consistent slope but vertical offset for minimal versus preferred flows. Close relationships between guidebook estimates of RF and Q_m were also observed for rivers in the American Rocky Mountain states of Idaho (r² = 0.55 and 0.74), Montana (r² = 0.34 and 0.80) and Colorado (r² = 0.43 and 0.51), but the association was weaker for the Pacific Northwest state of Oregon (r² = 0.35 and 0.26). These analyses indicate that RF can be confidently determined through a combination of subjective and hydraulic methods and reveal that RF values represent a systematic function of discharge for a broad range of alluvial and constrained river reaches. From these analyses we provide the ‘Alberta equation’: minimal recreational flow = 3 × Q_m^0.59 (Q_m in m³/s), and preferred flows would typically be 1.5 times higher. For other river regions the exponent ‘0.59’ may be relatively constant but adjustments to the coefficient ‘3’ could be applicable. Copyright © 2005 John Wiley & Sons, Ltd.