Nitrate removal in the hyporheic zone of a salmon river in Alaska

Pacific boreal streams and riparian zones are believed to receive significant N loads that are derived from the ocean in the form of decaying sockeye salmon (Oncorhynchus nerka). Using a small stream in south‐central Alaska we examined whether the associated riparian forest could take up the pulse of marine‐derived nitrogen (MDN) entering the hyporheic zone from spawning and dying sockeye salmon. We evaluate the relative importance of riparian uptake and denitrification in nitrate‐N removal in hyporheic sediment. We found that maximum biological removal of nitrate peaked within 1 h of water entering the hyporheic zone, decreasing exponentially with subsurface flow duration. Plant and microbial uptake reached 14 µg NO‐N L^?1 min^?1 and denitrification reached 4 µg NO‐N L^?1 min^?1 during the initial 2 h of transit time. Our results reinforce the hypothesis that MDN from Pacific salmon can be transferred to riparian zone via hyporheic flow. Most nitrate‐N removal along hyporheic flow paths is by plant and microbial uptake (the respective contributions could not be determined). Denitrifying bacteria are present and active in the hyporheic zones of this well‐oxygenated Alaskan stream but their contribution to the nitrate‐N removal is small compared to plant and microbial uptake in such nitrate‐N poor environment. Copyright © 2008 John Wiley & Sons, Ltd.     

Patterns in groundwater nitrogen concentration in the riparian zone of a large semi‐arid river (River Murray,Australia)

Lateral exchanges of surface water between river channels and their floodplains are important for vegetation health and aquatic food‐web productivity in semi‐arid ecosystems. However, the significance of the lateral connectivity via sub‐surface pathways in these systems is not as well understood. Patterns in nitrogen concentration in groundwater and in the unsaturated zone were used to infer the sub‐surface biogeochemistry of N in the riparian zone of a large semi‐arid floodplain (Hattah‐Kulkyne National Park) of the River Murray, Australia. The riparian zone plays a special role in this system as it is an area of transition between fresh surface waters and saline floodplain groundwater. The river was losing water to the floodplain during baseflow conditions but gradients were temporarily reversed following floods. In general, the redox conditions were sub‐oxic to anoxic in riparian groundwater and the main forms of N present were NH and dissolved organic N. There was a gradient in NH concentration from the river to the floodplain, suggesting that the main source of NH was from the decomposition of organic matter in fluvial sediments. Elevated concentrations of NO were occasionally found in shallow groundwater away from the river following floods but tended not to persist. The source of the NO appeared to be unsaturated‐zone NO displaced to the water table during floods. Assuming that denitrification was the main attenuation process, this displacement of unsaturated zone NO to anoxic groundwater could be a significant N removal process from the ecosystem (estimated at 18 kg N ha^?1 for the largest flood during the study). Understanding the impact of river regulation on floodplain nutrient cycles in River Murray floodplains will be challenging because the changes in floodplain hydrology are complex and coincide with salinization of soils and groundwater. Copyright © 2005 John Wiley & Sons, Ltd.     

Nitrogen dynamics in sediment during water level manipulation on the Upper Mississippi River

Nitrogen (N) has been linked to increasing eutrophication in the Gulf of Mexico and as a result there is increased interest in managing and improving water quality in the Mississippi River system. Water level reductions, or ‘drawdowns’, are being used more frequently in large river impoundments to improve vegetation growth and sediment compaction. We selected two areas of the Upper Mississippi River system (Navigation Pool 8 and Swan Lake) to examine the effects of water level drawdown on N dynamics. Navigation Pool 8 experienced summer drawdowns in 2001 and 2002. Certain areas of Swan Lake have been drawn down annually since the early 1970s where as other areas have remained inundated. In the 2002 Pool 8 study we determined the effects of sediment drying and rewetting resulting from water level drawdown on (1) patterns of sediment nitrification and denitrification and (2) concentrations of sediment and surface water total N (TN), nitrate, and ammonium (NH). In 2001, we only examined sediment NH and TN. In the Swan Lake study, we determined the long‐term effects of water level drawdowns on concentrations of sediment NH and TN in sediments that dried annually and those that remained inundated. Sediment NH decreased significantly in the Pool 8 studies during periods of desiccation, although there were no consistent trends in nitrification and denitrification or a reduction in total sediment N. Ammonium in sediments that have dried annually in Swan Lake appeared lower but was not significantly different from sediments that remain wet. The reduction in sediment NH in parts of Pool 8 was likely a result of increased plant growth and N assimilation, which is then redeposited back to the sediment surface upon plant senescence. Similarly, the Swan Lake study suggested that drawdowns do not result in long term reduction in sediment N. Water level drawdowns may actually reduce water retention time and river‐floodplain connectivity, while promoting significant accumulation of organic N. These results indicate that water level drawdowns are probably not an effective means of removing N from the Upper Mississippi River system. Copyright © 2006 John Wiley & Sons, Ltd.     

Water quality in the southern Tibetan Plateau: chemical evaluation of the Yarlung Tsangpo (Brahmaputra)

Yarlung Tsangpo (Brahmaputra) is the largest river system draining the northern slopes of the Himalayan ranges on the southern Tibetan Plateau. It remains one of only two large non‐regulated rivers in China. In this paper the chemical composition of Yarlung Tsangpo and its major tributaries (Raga Tsangpo, Nyangchu and Lhasa River) are studied. Water samples (n = 55) were collected and measured for major ions, trace elements and nutrients in order to: (1) define the present chemical quality of this water course; (2) address possible mechanisms governing the water chemical compositions, and (3) identify potential sources for contaminants. Multivariable analysis shows that geology and climate are the major explanatory variables for the spatial variation in water chemistry in this river system. In general, water chemistry is mainly controlled by carbonate weathering, with Ca²⁺ and HCO being the dominant ions. In addition, runoff from brackish/saline lakes and geothermal waters, enriched in Na⁺, Cl^?, SO, Mg²⁺ and Li, are major contributors of elevated concentrations of these solutes in the headwater regions resulting in a relatively high loading of total dissolved solids (TDS, 146–397 mg L^?1). Levels of most heavy metals and total dissolved nutrients were generally found to be low. However, elevated As concentration (avg. 95 μg L^?1) in the headwaters and additions from untreated wastewater were evident at some locations. Copyright © 2009 John Wiley & Sons, Ltd.     

Seasonal variation in nutrient retention during inundation of a short‐hydroperiod floodplain

Floodplains are generally considered to be important locations for nutrient retention or inorganic‐to‐organic nutrient conversions in riverine ecosystems. However, little is known about nutrient processing in short‐hydroperiod floodplains or seasonal variation in floodplain nutrient retention. Therefore, we quantified the net uptake, release or transformation of nitrogen (N), phosphorus (P) and suspended sediment species during brief periods (1–2 days) of overbank flooding through a 250‐m floodplain flowpath on the fourth‐order Mattawoman Creek, Maryland U.S.A. Sampling occurred during a winter, two spring and a summer flood in this largely forested watershed with low nutrient and sediment loading. Concentrations of NO increased significantly in surface water flowing over the floodplain in three of the four floods, suggesting the floodplain was a source of NO. The upper portion of the floodplain flowpath consistently exported NH, most likely due to the hyporheic flushing of floodplain soil NH, which was then likely nitrified to NO in floodwaters. The floodplain was a sink for particulate organic P (POP) during two floods and particulate organic N and inorganic suspended sediment (ISS) during one flood. Large releases of all dissolved inorganic N and P species occurred following a snowmelt and subsequent cold winter flood. Although there was little consistency in most patterns of nutrient processing among the different floods, this floodplain, characterized by brief inundation, low residence time and low nutrient loading, behaved oppositely from the conceptual model for most floodplains in that it generally exported inorganic nutrients and imported organic nutrients. Published in 2007 by John Wiley & Sons, Ltd.     

Seasonal and spatial variations in major and trace elements in a regulated boreal river (Esse River) affected by acid sulphate soils

In coastal areas of Finland, extensive artificial drainage of Holocene sulphide‐bearing marine and lacustrine sediments has resulted in development of acid sulphate (AS) soils (pH 2.5–4.5) over an estimated area of approximately 3000 km². During heavy rains and snow melting, these soils are flushed resulting in discharge of acidic and metal‐rich waters that strongly affect small streams. However, the total and precise effects in the important and large rivers are not well understood. In this study, the impact of AS soil occurrence and hydrological changes on water quality was determined in an important regulated boreal river (Esse River) having a catchment area of 2054 km² partially covered with AS soil (39 km²). Water samples, collected at five sites along the river during four carefully selected events, were analysed for pH, total organic carbon, conductivity and the following elements/anions: Al, Ba, Br, Ca, Cd, Cl^?, Co, Cr, Cu, Fe, K, La, Mg, Mn, Na, Ni, NO, Rb, Sc, Si, SO, Sr, Th, Y and Zn. There is a clear spatial correlation between AS soil occurrence and elevated element concentrations in the river water, especially when the conditions change from dry/warm (summer) to wet/cool (autumn). During the rains in autumn these soils are extensively flushed and concentrations of Co, La, Zn, Y, Mn and Al are increased between three and nine times towards the outlet. The buffering capacity of the river was, however, high enough to prevent a detrimental drop in pH. Another intriguing feature is substantially elevated concentrations of several potentially toxic metals (Cr, Cd, Cu) in the middle reaches in winter when the river is ice‐covered. Since no external source for this was found, we suggest an internal source operating by an as yet unknown mechanism. During baseflow in summer, the concentrations of several solutes reach minimum concentrations. Copyright © 2005 John Wiley & Sons, Ltd.     

Selecting Between One‐Dimensional and Two‐Dimensional Hydrodynamic Models for Ecohydraulic Analysis

Aquatic habitat assessment and river restoration design require geospatially explicit maps of hydraulic conditions. Diverse mechanistic ecohydraulic models compute spatially explicit depth and velocity results to evaluate habitat suitability spatially as a function of these abiotic conditions. This study compared depth and velocity results from two‐dimensional (2D) and one‐dimensional (1D) hydraulic models with algorithms that laterally discretize 1D velocity and interpolate depth and velocity spatially based on the Laplacian heat mapping approach. These ‘conveyance distributed’ methods constitute ‘best 1D modelling practice’ and were compared with 2D results for the first time. The 1D and 2D models were applied to three morphologically distinct reaches (leveed, meandering, and anastomosing) for three flows (base, bankfull, and flood flows) of the partially regulated, gravel/cobble lower Yuba River in north–central California. The test metrics were the coefficient of determination (R²) and the median absolute residual ( ). These metrics quantified the incremental uncertainty 1D approximation incurs, results which make explicit cost–benefit processes of model selection possible. Finally, velocity residual maps were analysed to identify regions and processes where residuals were high, indicating divergence from the 1D assumptions. Paired data (1D–2D) fell between 0.94 ≥ R² ≥ 1.00 (R²_mean = 0.98 and R²_median = 0.99) for depth and median absolute residuals were all 3.8 ≤ ≤ 7.2% (i.e. 50% of residuals are approximately within ±1.7 to 3.6%). Higher flows and lower gradient reaches had lower residuals and higher R². Velocity diverged more, particularly for base flow in anastomosing reaches (0.42 < R² < 0.58). One‐dimensional, conveyance distributed, assumptions performed better for other channel types, where 0.69 < R² < 0.81 (R²_mean = 0.75 and R²_median = 0.77), with median absolute residuals between 9.6% > > 22.4% (i.e. ~ ± 4.6 to ±11.2%), where _mean = 14.2% and _median = 13% (~ ±7.1 and 6.5%). The conveyance distributed 1D velocity model performed best, where the orthogonal flow assumptions obtained and where side channels did not transition from backwater to conveying area between flows. Copyright © 2015 John Wiley & Sons, Ltd.     

Impact of an urban centre on the nitrogen cycle processes of epilithic biofilms during a summer low‐water period *

Nitrogen transformations in epilithic biofilms of a large gravel bed river, the Garonne, France, has been studied upstream (one site) and downstream (four sites) of a large urban centre (Toulouse, 740 000 inhabitants). High biomass, up to 49 g AFDM m^?2 (ashes free dry matter) and 300 mg chlorophyll a m^?2 (Chl. a), were recorded at 6 and 12 km downstream from the main wastewater treatment plant outlet. The lowest records upstream and larger downstream (less than 16 g AFDM m^?2 or 120 mg Chl. a m^?2) could be explained by recent water fall (early summer low‐water period). Measurements of nitrogen exchange at the biofilm–overlying water interface were performed in incubation chambers under light and dark conditions. The addition of acetylene at the mid‐incubation time allowed evaluation of both nitrification (variation in NH₄⁺ flux after the ammonium monooxygenase inhibition) and denitrification (N₂O accumulation related to the inhibition of N₂O reduction). Denitrification (D_w) and nitrification rates were maximum at sites close to the city discharges in dark conditions (up to 9.1 and 5.6 mg N m^?2 h^?1, respectively). Unexpected denitrification activities in light conditions (up to 1.4 mg N m^?2 h^?1) at these sites provided evidence for enhanced nitrogen self‐purification downstream. As confirmed by most probable number (MPN) counts, high nitrification rates in biofilm close downstream were related to enhanced (more than almost 3 log) nitrifying bacteria densities (up to 7.6×10⁹ MPN m^?2). Downstream of an urban centre, nitrogen transformations in the biofilm appeared to be influenced by the occurrence of an adapted microflora which is inoculated or stimulated by anthropic pollution. Copyright © 2002 John Wiley & Sons, Ltd.     

Microbial processes at the land–water interface,and cross‐domain causal relationships,as influenced by atmospheric deposition of pollutants in three freshwater lakes in India

The effects of long‐term atmospheric deposition of pollutant elements on the trans‐surface causative relationships at three lake sites having different catchment characteristics were investigated in this study. The selected determinants included lake productivity, bottom sediment quality, and a suite of microbial variables (microbial biomass (C_mic); basal respiration; substrate‐induced respiration; bacterial:fungal ratio; metabolic quotient; and alkaline phosphatase and FDAase activities) measured at the land–water interface, in relation to atmospheric deposition of phosphate; nitrate; ammonium; sulphate; calcium; and magnesium. The results indicated significant between‐site differences (P < 0.001) in the atmospheric deposition of phosphate (0.21–1.96 kg.h^?1.year^?1); nitrate (2.77–28.05 kg.h^?1.year^?1); ammonium (0.58–11.60 kg.h^?1.year^?1); sulphate (5.64–32.15 kg.h^?1.year^?1); calcium (4.50–30.00 kg.h^?1.year^?1); and magnesium (1.50–12.15 kg.h^?1.year^?1), as well as a consistently increasing input of these ions across time. The catchment vegetation had important effects on microbial variables that, in turn, affected lake productivity. Interfaces of woodland lake were found to be rich in phenolics, supporting low C_mic and activities. Except for alkaline phosphatase, which declined over time, atmospheric deposition of pollutant elements increased the C_mic and activities at the land–water interface. The time lag correlation analysis indicated the C_mic and lake productivity relationships were significantly altered by atmospherically driven nitrogen and phosphorus inputs, with a time lag of 2–3 years. Despite being supportive, aerial nutrient inputs appeared to have a destabilizing effect on both, microbial biomass and lake productivity variables. These observations indicate that if present atmospheric deposition trends of pollutant elements continue, it will modify the cross‐domain causative relationships of inland lentic systems over the long term. These study results are relevant for the formulation of strategies for managing freshwater tropical lakes.     

Role of Local Flow Conditions in River Biofilm Colonization and Early Growth

Direct numerical simulations of a turbulent boundary layer flow over a bed of hemispheres of height h are performed using an immersed boundary method for comparison with river biofilm growth experiments performed in a hydraulic flume. Flow statistics above the substrates are shown to be in agreement with measurements performed by laser Doppler velocimetry and particle image velocimetry in the experiments. Numerical simulations give access to flow components inside the roughness sublayer, and biofilm colonization patterns found in the experiments are shown to be associated with low shear stress regions on the hemisphere surface. Two bed configurations, namely staggered and aligned configurations, lead to different colonization patterns because of differences in the local flow topology. Dependence with the Reynolds number of the biofilm distribution and accrual 7 days after inoculum is shown to be associated to local flow topology change and shear stress intensity. In particular, the shear stress τ on the surface of the hemispheres is found to scale as , where Re_t = u^*h/ν, with u^* as the log law friction velocity and ν as the fluid kinematic viscosity. This scaling is due to the development of boundary layers along the hemisphere surface. Associated with a critical shear stress for colonization and early growth, it explains the increasing delay in biomass accrual for increasing flow velocities in the experiments. Copyright © 2014 John Wiley & Sons, Ltd.     

An Estimate of Basin‐Wide Denitrification Based on Floodplain Inundation in the Atchafalaya River Basin,Louisiana

Maximizing the reduction of nitrate to dinitrogen gas (denitrification) has been advocated as a means to decrease nitrate pollution that causes eutrophication and hypoxia in estuaries worldwide. Managing this flux in bottomland forest wetlands of the Mississippi River could potentially reduce the world's second largest hypoxic zone. We used published denitrification rates, geospatial data on habitat area and inundation frequency, water level records (1963–2011), and average monthly temperatures to estimate annual denitrification in the Atchafalaya River Basin, the principal distributary of the Mississippi River. Denitrification rates ranged from 5394 kg N year^?1 (3.07 kg N km^?2 year^?1) in 1988 to 17 420 kg N year^?1 (9.92 kg N km^?2 year^?1) in 1981, and rates were consistently higher in fall compared with those in spring. Total NO₃^? denitrified in the basin was negligible compared with total NO₃^? entering the Gulf of Mexico. If all N denitrified in the basin instead entered the Gulf, the hypoxic zone was predicted to increase only 5.07 km² (0.06%). This negligible effect of the basin on N dynamics in the Gulf agrees with other mass balance and isotopic studies in the region. Copyright © 2014 John Wiley & Sons, Ltd.     

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]     

Erratum: Predicting the morphological and hydraulic consequences of river rehabilitation

Erratum : Predicting the Morphological and Hydraulic Consequences of River Rehabilitation. S. Schweizer, M. E. Borsuk and P. Reichert . River Research and Applications (23)3: 303–322. Equation 17 on page 313 should read and not as published.     

Errors of kinematic-wave and diffusion-wave approximations for time-independent flows

Time-independent (or steady-state) cases of planar (overland) flow were treated. Errors of the kinematic-wave and diffusion-wave approximations were derived for three types of boundary conditions: zero flow at the upstream end, and critical flow depth and zero depth-gradient at the downstream end. The diffusion wave approximation was found to be in excellent agreement with the dynamic wave approximation, with error in the range of 1–2% for values ofKF ₀ ² (7.5). Even for small values ofKF ₂ ⁰ (e.g.,KF ₂ ⁰ =0.75), the errors were typically in the range of 11–15%. The accuracy of the diffusion wave approximation was greatly influenced by the downstream boundary condition. The error of the kinematic wave approximation was found to vary from 7 to 13% in the regions 0.05x0.95 forKF ₀ ² =0.75 and was greater than 30% forKF ₀ ² =0.75.     

Anaerobic microbial metabolism in hyporheic sediment of a gravel bar in a small lowland stream

Distribution of dissolved oxygen, nitrate, sulphate, carbon dioxide and dissolved organic carbon (DOC), acetate and lactate was studied in the stream and interstitial water along the subsurface flowpath in the hyporheic zone of a small lowland stream. Sediments were found to act as a source of nitrous oxide and methane. Interstitial methane concentrations were significantly much higher in comparison to those from surface water, and were significantly lower in the relatively well oxygenated downwelling zone than in the rather anoxic upwelling zone. The interstitial concentrations of O₂, NO₃^?1 and SO₄^?2 showed significant decline along the subsurface flowpath, while concentrations of CO₂, N₂O, DOC, acetate and lactate remained unchanged. In addition to field measurements, ex situ incubation of sediments was carried out in the laboratory. Maximal methane production was found in the incubation assay using acetate (mean value 380 µg CH₄ kg DW^?1 d^?1). Mean value of the denitrification potential was 1.1 mg N₂O kg DW^?1 d^?1. Nitrous oxide production potential reached 71–100% of denitrification potential. Our results demonstrate that respiration of oxygen, nitrate, sulphate and methanogenesis may coexist within the hyporheic zone and that anaerobic metabolism is an important pathway in organic carbon cycling in the Sitka stream sediments. Copyright © 2005 John Wiley & Sons, Ltd.     

Growth,mortality and recruitment of Nile perch (Lates niloticus) in Lake Victoria,Kenya

This study investigated the growth, mortality and recruitment of Lates niloticus in Lake Victoria basis on length–frequency data collected during the period 2014‐2015. The asymptotic length (L _∞ ) had a value of 124 cm TL , growth curvature (K ) of 0.22 year^?1, total mortality (Z ) of 0.96 year^?1, a natural mortality (M ) of 0.42 year^?1, a fishing mortality (F ) of 0.54 year^?1, an exploitation rate (E ) of 0.57 and a growth performance index () of 3.53. Logistic selection model showed that 50% of fish of 46.09 cm TL encountering the gear are retained. There were two peak recruitment periods, a minor one in March and a major one in July, accounting for 12.04% and 22.04%, respectively, of the total fish catch. The Beverton and Holt's relative yield‐per‐recruit model indicated the indices for sustainable yields are 0.32 for optimum sustainable yield (E _0.5), 0.60 for maximum sustainable yield (E _max) and 0.51 for economic yield (E _0.1). Compared to previous findings, there is a great decline in the sizes of Nile perch stocks in Lake Victoria. Thus, managing the fishery requires strict adherence to the slot size of 50–85 cm TL , and restrictions on illegal gear and methods, by the devolved governments through monitoring, control and surveillance in liaison with the Beach Management Units (BMU s).     

Anaerobic processes in activated sludge

We found anoxic zones in aerated activated sludge flocs, and demonstrated denitrification under normal operating conditions. Sulfate reduction was not found. Micro-environments and microbial conversions in flocs from bulking and non-bulking activated sludge were determined with microsensors for H₂S, O₂, NO₂₋ and NO₃₋. Denitriftcation and sulfate reduction rates were measured with ¹⁵N- and ³⁵S-tracer techniques. We showed that under normal reactor conditions (ca. 20% air saturation) anoxic zones develop within flocs allowing denitrification. The denitrtftcation rates amounted to 40% of the rates under anoxic conditions. At 100% air saturation no anoxic zones were found and no denitrification occurred. However, in flocs from bulking sludge (at 20% air saturation) anoxic zones were absent and denitrification did not occur. In bulking sludge only at total anoxia was denitrification found. Confocal microscopy showed that flocs from bulking sludge were much looser than those from non-bulking sludge. The absence of anoxic zones and of denitrification was attributed to the open floc structure, allowing advective oxygen transport.Sulfate reduction was not detected in any of the sludges tested by microsensors or by tracer techniques even under anoxic conditions. This indicates that the sulfur cycle (sulfate reduction and sulfide oxidation) does not play a role in mineralization processes and bulking in activated sludge. Preliminary molecular work (in situ hybridization with the 16S-rRNA probe SRB385) indicated the presence of small amounts of sulfate reducing bacteria in all sludges. Either the probe is not specific or the sulfate reducers present are not active under reactor conditions.     

A variable sorptivity infiltration equation

Horizontal and vertical one-dimensional infiltration are compared when they both occur in a homogeneous isotropic porous body initially at a uniform low water content _n under constant concentration (₀) or constant pressure head (H ₀) conditions. From a consideration of the physics governing infiltration under such conditions, the conclusion is reached that the magnitude of the pressure head gradient atx=0, wherex=0 denotes the infiltration surface in the horizontal case, must be larger than the magnitude of the pressure head gradient atz=0, wherez=0 denotes the infiltration surface in the vertical case, for all finitet>0, so that for the hydraulic head gradient atz=0 to be greater than (1/2K ₀)S _x t ^–1/2 but smaller than [(1/2K ₀)S _x t ^–1/2+1],K ₀ being the hydraulic conductivity at ₀ andS _x the sorptivity during horizontal infiltration. On these grounds, it is further argued that if the sorptivityS _z is introduced for the case of vertical infiltration, then it must be equal toS _x fort=0 only and that it must decrease with time. Results obtained by solving soil-water flow equations for the infiltration conditions defined above, and from experiment, support the above conclusions. An equation for the relationship between cumulative infiltration and time during vertical infiltration is developed after assuming thatS _z decreases with time in an exponential manner. Cumulative infiltration versus time relationships given by this equation are compared with those obtained from the numerical solution of the soil-water flow equation and from experiment.     

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     

A real-time flood forecasting model based on maximum-entropy spectral analysis: I. Development

This paper, the first of two, develops a real-time flood forecasting model using Burg's maximum-entropy spectral analysis (MESA). Fundamental to MESA is the extension of autocovariance and cross-covariance matrices describing the correlations within and between rainfall and runoff series. These matrices are used to derive the model forecasting equations (with and without feedback). The model may be potentially applicable to any pair of correlated hydrologic processes.Notation a _k extension coefficient of the model atkth step - B _k backward extension matrix forkth step - B _ijk element of the matrixB _k (i,j=1, 2) - c _k coefficient of the entropy model atkth step in the LB algorithm - e _k (e _x ,e _y )k = forecast error vector atkth step - E _k error matrix atkth step - E _ijk element of theE _k (i,j=1, 2) - f frequency - F _k forward extension matrix atkth step - F _ijk element of theF _k matrix (i,j=1, 2) - H(f) entropy expressed in terms of frequency - H _X entropy of the rainfall process (X) - H _Y entropy of the runoff process (Y) - H _XY entropy of the rainfall-runoff process - I identity matrix - forecast lead time - m model order, number of autocorrelations - R correlation matrix - S _x standard deviation of the rainfall data - S _y standard deviation of the runoff data - t time - T ₁ rainfall record - T ₂ runoff record - T rainfall-runoff record (T=T ₁ T ₂) - x _t rainfall data (depth) - X X() = rainfall process - mean of the rainfall data - y _t direct runoff data (discharge) - Y Y() = runoff process - mean of the runoff data - (x, y) _t rainfall-runoff data (att T) - (x, y, z) _t rainfall-runoff-sediment yield data (att T) - z complex number (in spectral analysis) - _k coefficient of the LB algorithm atkth step - _nj Lagrange multiplier atjth location in the _n matrix - _{n n} = matrix of the Lagrange multiplier atkth step - _X (k), _Y (k) autocorrelation function of rainfall and runoff processes atkth lag - _XY (k) cross-correlation function of rainfall and runoff processes atkth lag - W ₁(f) power spectrum of rainfall or runoff - W ₂(f) cross-spectrum of rainfall or runoff Abbreviations acf autocorrelation function - ARMA autoregressive moving average (model) - ARMAX ARMA with exogenous input - ccf cross-correlation function - det() determinant of the (...) matrix - E[...] expectation of [...] - FLT forecast lead time - KF Kalman filter - LB Levinson-Burg (algorithm) - MESA maximum entropy spectral analysis - MSE mean square error - SS state-space (model) - STI sampling time interval - forecast ofx - forecast ofx -step ahead - x _F feedback ofx-value (real value) - |x| module (absolute value) ofx - X ^–1 inverse of the matrixX - X* transpose of the matrixX