Runoff processes in glacier and páramo catchments in the Andean region are of interest as they are vitally important to serve the water needs of surrounding communities. Particularly in Northern Ecuador, the runoff processes are less well-known due to the high variability of precipitation, young volcanic ash soil properties, soil moisture dynamics and other local factors. Previous studies have shown that the melting of glaciers contributes to runoff generation and that the páramo ecosystem plays an important role in regulating runoff during periods of low precipitation. Data collection and experimental investigations were carried out in a catchment of 15.2 km² and altitude ranging between 4000 and 5700 m above sea level. Environmental tracers and hydrochemical catchment characterization were used for identifying runoff sources and their respective contributions during dry and wet conditions. Dry conditions are defined as periods where precipitation was absent for at least three consecutive days and wet conditions imply rainfall events. This study highlights the importance of the páramo on contributing to total runoff during baseflow (70% of total runoff) and the capacity of the páramo to dissipate the stream energy and buffer the peak flow during rainfall conditions. Electrical conductivity together with stable isotopes were identified as conservative tracers that characterize the end-member concentrations.

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Flood watermarks stipulate peak water depths from a flood event, indicating a magnitude of inundation that took place. Such information is invaluable for instantiation and validation of urban flood models. However, collecting and processing such data from land surveys can be costly and time-consuming. New remote sensing and data processing technologies offer improved opportunities to address these issues. The present paper deals with the new structure from motion (SfM) technology and its application in extracting flood watermarks. For this purpose, the first of its kind, side-view SfM surveys with two mobile units were utilised. Survey works were carried out in the vicinity of Ayutthaya heritage area (Thailand) and data obtained were used for setting up numerical models and simulations of the 2011 flood event. The work undertaken demonstrates the significant capability of SfM technology for extraction of flood watermarks. With such technology, it was possible to indicate façades, low-level structures, and susceptible openings, which in turn have improved schematizations of two-dimensional (2D) flood models. The resulting model simulations were found to be more accurate (i.e., more close to the measurements of flood watermarks) than those obtained from models with conventional top-view light detection and ranging (LiDAR) data.@en

Efficient management of a sewer system includes the control of the conveyed wastewater quality to adequately operate treatment plants and protect the receiving water bodies. Moreover, these systems are vulnerable to either accidental spills or intentional unauthorized discharges. To properly manage them, a limited number of sensors could be placed at different locations to monitor the water quality. In this paper, multiobjective and single-objective optimization procedures to optimally locate sensors in sewer systems are proposed, tested, and compared. The multiobjective procedures include objective functions related to information theory (IT procedure), detection time and reliability (DR procedure), and a combination of them (IT_DR procedure). The single-objective procedures include a greedy-based objective function (GR procedure) and a merged objective function (DR_IT_GR procedure). The procedures show a similar performance when applied on a small network, whereas in a real system, the results show that (1) the IT-based method can be effectively used as a filtering technique(2) the DR_IT_GR procedure outperforms the other multiobjective onesand (3) the GR procedure is very efficient in finding the Pareto extreme solutions.

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Riparian zones have significant impact on nitrate removal despite their small areas. Most research on riparian zones have been implemented at small scales. Direct measurement at large scale is infeasible, thus using models is a good alternative. This study introduces a modified SWAT model, referred as SWAT_LS. Two modifications were implemented: (i) adding hydrological routing from upland areas to riparian zones; and (ii) adding a module to simulate denitrification in riparian zones based on the Riparian Nitrogen Model. SWAT_LS was applied to the Odense river basin in Denmark, a densely tile-drained agricultural river basin. Compared to SWAT, SWAT_LS provides an equally good performance for streamflow, and a significant improvement in nitrate predictions. SWAT_LS predicts that current riparian zones remove only 4–17% of nitrate loads because 70% of the riparian areas are bypassed due to subsurface drainage implementation. This ability would dramatically increase to 25–85% if riparian zones are entirely undrained.

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The Ribb River is one of the components of the  Blue Nile River system located in the North  Western part of Ethiopia. It drains to Lake  Tana, the source of the Blue Nile River. The  Ribb has a length of 130 km, with a catchment  area of 1,812 km2. The average yearly rainfall  of the catchment is 1300 mm, with 80 %  occurring between the months of June and  September. The average and daily maximum  discharge of the river are 15 m3/s and 220  m3/s, respectively. A large dam and a diversion  weir 30 km downstream of the dam are under  construction to irrigate 15,000 ha of Fogera  flood plain (WWDSE and TAHAL, 2007).  Downstream of the dam location, the Ribb is a  meandering river with slope ranging from  0.18% to 0.03%. The river bed material is  dominated by sand with a gravel component in  its upper reaches. Intensive agriculture without  any natural resources conservation,  deforestation, dike construction, pump  irrigation and sand mining are the most  impactful activities in the Ribb watershed  (Tarekegn et al., 2010; Garede and Minale,  2014). The Lake Tana level is regulated since  1995 for hydropower production, which  enhances flooding along the lower river reach.  During the 2006 event, 45 people died, 30,000  persons were displaced and 5371 ha of  agricultural land were inundated (ENTRO,  2010). To prevent flooding, dikes have been  constructed in the lower reach of the river.  This study aims to describe current river  morphodynamic trends, including planimetric  changes for the definition of the pre-dam  conditions of the river. The first part of the work  is presented here with some preliminary  results, focusing on the river planimetric  changes. This paper describes the initial state  of the study.  @en

Many terrestrial biogeochemistry process models have been applied around the world at different scales and for a large range of ecosystems. Despite being essential ecosystems that sustain important ecological processes, only a few efforts have been made to estimate the gross primary production (GPP) and the hydrological budgets along an altitudinal gradient for grasslands in the Andean Region. One of the few previous studies in the region considered the heterogeneity of the main properties of the páramo vegetation and showed significant differences in plant functional types, site/soil parameters, and daily meteorology. This study extends the work previously mentioned by using the Biome-BGC model to simulate the GPP and the water fluxes in a representative area of the Ecuadorian Andean páramos. It focuses on three main growth forms of vegetation and is also extended to cells with similar properties. The responses of GPP and the water fluxes were dependent on environmental drivers, ecophysiology, and site-specific parameters. The results showed that the GPP estimations at lower elevations are more than twice the estimations at higher elevations, which might have a large implication during extrapolations at larger spatiotemporal scales. The assessment of the water fluxes in the páramo ecosystem was inaccurate, presumably due to the poor estimation of the soil processes, water storage, and evaporative processes. A further development in the soil and evaporative modeling process of Biome-BGC is needed in order to be fully applicable in the high-altitudinal páramo ecosystems. An accurate estimation of the temporal changes of carbon and water budgets can potentially assess the effect of the climate drivers in the biomass productivity of this terrestrial ecosystem.@en

Response strategies determine the resilience of an area to effects of sea level rise. Strategies that are sustainable are those that do not negatively affect the environment, biodiversity and community life of the people. The paper discusses response strategies practiced in the Niger delta to combat effects of sea level rise like: flooding, erosion, inundation, storm surge, and intrusion of sea salt. Local responses to these natural hazards and the degree of effectiveness of the methods in enabling the people return to their normal lives are reviewed for their suitability as future adaptation strategies. GIS and remote sensing analysis of slope and topography show the Niger delta is vulnerable to further flooding, inundation, and erosion as a result of sea level rise. Based on a ‘business as usual’ scenario, the GIS based bathtub approach is used to calculate and map possible inundation extents for the Niger delta under sea level rise conditions. As the Niger delta is subsiding due to oil and gas exploitation, relative sea level rise (RSLR) values for the Niger delta are obtained by adding measured subsidence values (7 mm and 25 mm) to predicted eustatic sea level rise values (19 mm by 2030 and 35 mm by 2050); resulting in RSLR of 0.14–0.96 m by 2030 and 2050. With subsidence at 7 mm/year and a RSLR of 0.14 m, results for 2030 shows an inundation extent of 1119.3 km² which is 4.6% of the total surface area; subsidence of 25 mm/year (SLR = 0.44 m) gives an inundation extent of 1254.0 km² which is 5.2% of the surface area. Results for 2050 show that a rise of 0.29 m (subsidence = 7 mm/year) will cause an inundation extent of 1175.9 km² which is 4.9% of the total surface area, and RSLR of 0.96 m (subsidence = 25 mm/year) inundates 1633.0 km² which is 6.8% of the surface area. Although the literature shows local practices have helped people to cope with the challenges posed by flooding, erosion, inundation, and inland intrusion of sea salts, however some of the practices have disadvantages that make them undesirable for inclusion in future planning. Sustainable local practices in the Niger delta include: planting of Bamboo trees for erosion control, use of sandbags as bridges and dikes (flood control), use of flood receptor pits as temporary flood water reservoirs, and community legislation against sand mining and indiscriminate tree felling. Further studies on the limitations of the local resilience practices in the Niger delta is recommended.

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Aims The importance of quantifying carbon stocks in terrestrial ecosystems is crucial for determining climate change dynamics. However, the present regional assessments of carbon stocks in tropical grasslands are extrapolated to unsampled areas with a high degree of uncertainty and without considering the carbon and nitrogen composition of vegetation and soil along altitudinal ranges. This study aims to assess carbon and nitrogen concentrations in soil and vegetation, aboveground carbon stocks distribution and soil organic carbon stocks along an altitudinal range in the páramo region in the Ecuadorian Andes. Methods The vegetation inventory was conducted using 15×15 m sampling plots distributed in three altitudinal ranges. Based on the patterns exhibited by the dominant vegetation growth forms, biomass and soil were sampled to quantify the corresponding carbon and nitrogen concentrations. Subsequently, the aboveground live biomass along the páramo altitudinal range was estimated using allometric equations. Finally, soil and vegetation carbon stocks were estimated for the entire basin. Important Findings Altitudinal analysis supported a potential distribution of carbon and nitrogen concentrations in soil, litter and live tissues, where higher concentrations were found in the low altitudinal range mainly for tussocks and acaulescent rosettes. Cellulose in litter showed higher concentrations at low altitudinal ranges for acaulescent rosettes and cushions only. For the same growth forms, lignin patterns in litter were higher in high altitudinal ranges. Soil texture provided complementary information: high percentage of silt was highly correlated to high soil nitrogen and carbon concentration. Tussocks were found to be responsive to altitude with their, highest aboveground carbon stocks occurring at the low altitudinal range, but cushions and acaulescent rosettes responded differently. The established relationships among soil, vegetation and altitude shown in this study must be taken into account to estimate both aboveground and soil organic carbon stocks in páramo regions - such estimates will be considerably inaccurate if these relationships are ignored.

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Severe flood events in China are a common cause of life losses. Many efforts have been carried out by the Yellow River Conservancy Commission (YRCC) to understand flood development and impact on the Yellow River. Modeling approaches based on discretization of the modeled domain in square and rectangular grids have great importance in the management of rivers, but they usually present two drawbacks: the required accuracy of the meandering of wide long rivers is not well represented, and the need to use many grid cells reduces computational speed. Modeling and simulation of extreme flood events using unstructured grids has not yet been applied to the Yellow River. This study shows how such a method can be beneficial to decision makers in the Yellow River region in case of flood events. The research shows that a flexible mesh discretization of the domain can overcome the two drawbacks. Along with a test of the proposed modeling method, new characteristics of the spatial evolution of flood events in the Yellow River emerged and are presented, showing the capabilities of DFloridaOW-FM software in modeling such a complex system.@en

Compared to coastal areas, river deltas which are located in coastal zone, have complex morphologies, because river waters and sediments are transported through the deltas into the sea. A delta can have many elements included, such as barrier islands, multiple estuaries, sand beaches, or mud coasts. It can be crisscrossed by rivers emanating from different sources and carrying different types of sediments; which differentiate the segments of the coast. Generally, deltas are fertile and highly productive, attracting agricultural activities and trade and thus densely populated. The physical properties of deltas and anthropogenic activities make them vulnerable to the effects of the changing climate; however when evaluation of vulnerabilities is important many coastal deltas lack even the most basic necessary data (e.g water level) for performing such a task. Data availability is one of the most important factors for analysis, assessment and modeling of physical and other phenomena related to river and coastal systems. Although lower Niger delta is classified as one of the deltas of the world vulnerable to the effects of climate change, it has little availability of data for hydrologic and hydraulic modeling. Present paper will show how to model the possible effect of a rise in sea levels on the lower Niger delta, by dividing its coastline into 54 segments based on slope, elevation and presence of large estuaries. The segments are analyzed for vulnerability to flooding, erosion and inundation. The parts identified as the most vulnerable are modeled using Deltares' DFlow modelling methodology, using a flexible mesh for discretization of the modeled area. Satellite derived DEM is used to calculate an upstream rating curve for the Bonny River, and to provide topographic data. Sea level rise is represented by changes in the tidal level to reflect IPCC predictions of sea levels by 2050 and 2100. The results are analyzed for flooding and inundation, increase in land loss, water depth and flood extent as compared with no sea level rise scenarios. Also, dry and wet land losses are mapped and quantified within a GIS environment.@en

This paper presents the mechanical and hydraulic behaviour of passively prestressed concrete-lined pressure tunnels embedded in elastic transversely isotropic rocks subjected to non-uniform in situ stresses. Two cases are distinguished based on whether the in situ vertical stress in the rock mass is higher, or lower than the in situ horizontal stress. A two-dimensional finite element model was used to study the influence of dip angle, α, and horizontal-to-vertical stress ratio, k, on the bearing capacity of prestressed concrete-lined pressure tunnels. The study reveals that the in situ stress ratio and the orientation of stratifications in the rock mass significantly affect the load sharing between the rock mass and the lining. The distribution of stresses and deformations as a result of tunnel construction processes exhibits a symmetrical pattern for tunnels embedded in a rock mass with either horizontal or vertical stratification planes, whereas it demonstrates an unsymmetrical pattern for tunnels embedded in a rock mass with inclined stratification planes. The results obtained for a specific value α with coefficient k are identical to that for α + 90° with coefficient 1/k by rotating the tunnel axis by 90°. The maximum internal water pressure was determined by offsetting the prestress-induced hoop strains at the final lining intrados against the seepage-induced hoop strains. As well as assessing the internal water pressure, this approach is capable of identifying potential locations where longitudinal cracks may occur in the final lining.

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This article presents a simulation-optimization approach for evaluating the feasibility of managed aquifer recharge (MAR) in the Samail Lower Catchment, Oman. The objective is to provide a maximum recharge and extraction rate through MAR in an annual cycle of two successive injection and recovery periods, while meeting operational and system constraints such as water level, gradient, and travel time. Three groundwater management problems were solved by coupling a simulation model with successive linear programming (SLP) and the nondominated sorting genetic algorithm (NSGA-II) multiobjective genetic algorithm. Sensitivity analysis was also completed to examine the overall response of the simulation-optimization results to changes in hydraulic conductivities and maximum injection rates. Results using the SLP algorithm showed that the total volume of injected water for 4 months of injection without recovery is as high as 8 × 106 m3, and the total recovered volume of water for 4 months injection and 8 months recovery is approximately 5.3 × 106 m3, giving a total recovery efficiency of approximately 66%. For the same setup the NSGA-II algorithm derived the entire nondominated front of solutions for two conflicting objectives: maximizing recovery rate and maximizing minimum groundwater head close to the sea (for preventing seawater intrusion). This algorithm includes travel time constraints directly in the optimization process. In conclusion, the proposed approach provides a cost-effective means to evaluate MAR in a coastal aquifer.
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Hydrological data collection requires deployment of physical infrastructure like rain gauges, water level gauges, as well as use of expensive equipment like echo sounders. Many countries around the world have recorded a decrease in deployment of physical infrastructure for hydrological measurements; developing countries especially have less of this infrastructure and, where it exists, it is poorly maintained. Satellite remote sensing can bridge this gap, and has been applied by hydrologists over the years, with the earliest applications in water body and flood mapping. With the availability of more optical satellites with relatively low temporal resolutions globally, satellite data are commonly used for mapping of water bodies, testing of inundation models, precipitation monitoring, and mapping of flood extent. Use of satellite data to estimate hydrological parameters continues to increase due to use of better sensors, improvement in knowledge of and utilization of satellite data, and expansion of research topics. A review of applications of satellite remote sensing in surface water modelling, mapping and parameter estimation is presented, and its limitations for surface water applications are also discussed.

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As one of the main areas of carbon cycle and climate change studies, water and CO2 relations are of great significance for estimation of gross primary production (GPP). Various biogeochemical process-based models have been set up to estimate the GPP based on mathematical representation of biological, physiological and ecological processes. However, they ended up increasing the complexity and computational processing power due to the large number of physical equations that need to be solved. Computational time becomes an important matter in the simulation of multiple scenarios using models for long periods of time (e.g. climate projections). Data driven surrogate models have proven to be a useful tool for environmental modelling especially when ecological and climatic co-variates are large. The advantages of Data Driven Models (DDM) are: the possibility of adding new independent variables even if their understanding is weak, and short computational time to run. The aim is to explore the ability of DDMs to replicate a biochemical model calculating GPP. This study evaluates the performance of four surrogate DDMs, namely linear regression method (LRM), model tree (MT), instance-based learning (IBL) and artificial neural network (ANN). A simple empirical and semi-empirical relationship between GPP and climatic variables are studied. Input variable selection (IVS) methods were used to decide on the most relevant and potential environmental model inputs and then followed by a two-step approach which included a model-free and a model-based technique. Data from the highlands (páramo ecosystem) in the Ecuadorian Andean Region from 12-year time-series (2000-2011) were used to evaluate the models at various time frames and at different altitudes. The GPP time series data for the same period were derived from an earlier study using the biomodel BIOME-BGC (BioGeochemical Cycles), which is a comprehensive physical based model used in different analysis of carbon fluxes around the world. So-called IBL (nearest neighbour method) showed a great capability to reproduce the GPP when data was aggregated to monthly time frame. The computational time used to evaluate the time series with IBL as the selected DDM is shorter with enough accuracy for using it in multi-model runs.@en

A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.

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Top-view data obtainedfrom LiDAR systemshas long been used as topographic-input data for urban flood modelling applications. This high-resolution input data has considerable potential to improve urban flood modelling predictions with more detail. However, the difficulty of employing top-view data is that it may create some missing urban features because this type ofdata cannot represent anyurban features,which are hiddenunderneath other objects. These hidden featuresmay play a substantial part in diverting floodwater flowing through,especially in complex urban areas. The recent advances in Photogrammetry and Computer Vision techniques offer an opportunity to create high-resolution topographic data. By using a consumer digital camera, 2D digital photoscan betaken from different viewpoints. The so-called Structure from Motion (SfM) techniquecan usethese overlappingphotos and reconstruct theminto3D pointcloud data with a high level of accuracy and resolution,usinga cost effective approach. In this work, we create street-view SfM point-cloud data obtained from street viewpoints. We also introduce a new multi-view approach by merging top-view LiDAR data withstreet-view SfM data. This new multi-view data can be used as topographic input data for a coupled 1D-2D model. When applyingsuch newdata, the flood simulation results can highlight some flood propagations much better than using the traditional top-view LiDAR data. Therefore, it has the potential toenhance the multi-view approach into practicable flood-modelling applications for the present and future urbanizing areas. @en