Integrated Catchment Model Research Articles

Simulating climate change and socio-economic change impacts on flows and water quality in the Mahanadi River system, India

Delta systems formed by the deposition of sediments at the mouths of large catchments are vulnerable to sea level rise and other climate change impacts. Deltas often have some of the highest population densities in the world and the Mahanadi Delta in India is one of these, with a population of 39 million. The Mahanadi River is a major river in East Central India and flows through Chattisgarh and Orissa states before discharging into the Bay of Bengal. This study uses an Integrated Catchment Model (INCA) to simulate flow dynamics and water quality (nitrogen and phosphorus) and to analyze the impacts of climate change and socio-economic drivers in the Mahanadi River system. Future flows affected by large population growth, effluent discharge increases and changes in irrigation water demand from changing land uses are assessed under shared socio-economic pathways (SSPs). Model results indicate a significant increase in monsoon flows under the future climates at 2050s (2041–2060) and 2090s (2079–2098) which greatly enhances flood potential. The water availability under low flow conditions will be worsened because of increased water demand from population growth and increased irrigation in the future. Decreased concentrations of nitrogen and phosphorus are expected due to increased flow hence dilution. Socio-economic scenarios have a significant impact on water quality but less impact on the river flow. For example, higher population growth, increased sewage treatment discharges, land use change and enhanced atmospheric deposition would result in the deterioration of water quality, while the upgrade of the sewage treatment works lead to improved water quality. In summary, socio-economic scenarios would change future water quality of the Mahanadi River and alter nutrient fluxes transported into the delta region. This study has serious implications for people's livelihoods in the deltaic area and could impact coastal and Bay of Bengal water ecology.

Water quality assessment and catchment-scale nutrient flux modeling in the Ramganga River Basin in north India: An application of INCA model

The present study analyzes the water quality characteristics of the Ramganga (a major tributary of the Ganga river) using long-term (1991–2009) monthly data and applies the Integrated Catchment Model of Nitrogen (INCA-N) and Phosphorus (INCA-P) to the catchment. The models were calibrated and validated using discharge (1993–2011), phosphate (1993–2010) and nitrate (2007–2010) concentrations. The model results were assessed based on Pearson's correlation, Nash-Sutcliffe and Percentage bias statistics along with a visual inspection of the outputs. The seasonal variation study shows high nutrient concentrations in the pre-monsoon season compared to the other seasons. High nutrient concentrations in the low flows period pose a serious threat to aquatic life of the river although the concentrations are lowered during high flows because of the dilution effect. The hydrological model is satisfactorily calibrated with R2 and NS values ranging between 0.6–0.8 and 0.4–0.8, respectively. INCA-N and INCA-P successfully capture the seasonal trend of nutrient concentrations with R2>0.5 and PBIAS within ±17% for the monthly averages. Although, high concentrations are detected in the low flows period, around 50% of the nutrient load is transported by the monsoonal high flows. The downstream catchments are characterized by high nutrient transport through high flows where additional nutrient supply from industries and agricultural practices also prevail. The seasonal nitrate (R2: 0.88–0.94) and phosphate (R2: 0.62–0.95) loads in the catchment are calculated using model results and ratio estimator load calculation technique. On average, around 548tonnes of phosphorus (as phosphate) and 77,051tonnes of nitrogen (as nitrate) are estimated to be exported annually from the Ramganga River to the Ganga. Overall, the model has been able to successfully reproduce the catchment dynamics in terms of seasonal variation and broad-scale spatial variability of nutrient fluxes in the Ramganga catchment.

Are the benefits of integrated catchment modelling being realized in the united kingdom?

Are the benefits of integrated catchment modelling being realized in the united kingdom?

Impact of Spatiotemporal Characteristics of Rainfall Inputs on Integrated Catchment Dissolved Oxygen Simulations

Integrated Catchment Modelling aims to simulate jointly urban drainage systems, wastewater treatment plant and rivers. The effect of rainfall input uncertainties in the modelling of individual urban drainage systems has been discussed in several studies already. However, this influence changes when simultaneously simulating several urban drainage subsystems and their impact on receiving water quality. This study investigates the effect of the characteristics of rainfall inputs on a large-scale integrated catchment simulator for dissolved oxygen predictions in the River Dommel (The Netherlands). Rainfall products were generated with varying time-aggregation (10, 30 and 60 min) deriving from different sources of data with increasing spatial information: (1) Homogeneous rainfall from a single rain gauge; (2) block kriging from 13 rain gauges; (3) averaged C-Band radar estimation and (4) kriging with external drift combining radar and rain gauge data with change of spatial support. The influence of the different rainfall inputs was observed at combined sewer overflows (CSO) and dissolved oxygen (DO) dynamics in the river. Comparison of the simulations with river monitoring data showed a low sensitivity to temporal aggregation of rainfall inputs and a relevant impact of the spatial scale with a link to the storm characteristics to CSO and DO concentration in the receiving water.

Influence of Rainfall, Model Parameters and Routing Methods on Stormwater Modelling

Quantification of the uncertainty associated with stormwater models should be analyzed before using modelling results to make decisions on urban stormwater control and management programs. In this study, the InfoWorks Integrated Catchment Modelling (ICM) rainfall-runoff model was used to simulate hydrographs at the outfall of a catchment (drainage area 8.3 ha, with 95% pervious areas) in Shenzhen, China. The model was calibrated and validated for two rainfall events with Nash-Sutcliffe efficiency >0.81. The influence of rainfall, model parameters and routing methods on outflow hydrograph of the catchment was systematically studied. The influence of rainfall was analyzed using generated rainfall distributions with random errors and systematic errors (± 30% offsets). Random errors had less influence than systematic errors on peak flow and runoff volume, especially for two rainfall events with larger depths and longer durations. The Monte Carlo simulations using 500 parameter sets were used to verify the equifinality of the nine model parameters and determine the prediction uncertainty. Most of the monitored flows were within the uncertainty range. The influence of two routing methods from rainfall excess to hydrograph was studied. The InfoWorks ICM model incorporating double quasilinear reservoir routing was found to have a larger effect on the simulated hydrographs for rainfall events having larger depths and longer durations than using the U.S. EPA’s Storm Water Management Model nonlinear reservoir routing method did.

Urban stormwater inundation simulation based on SWMM and diffusive overland-flow model.

With rapid urbanization, inundation-induced property losses have become more and more severe. Urban inundation modeling is an effective way to reduce these losses. This paper introduces a simplified urban stormwater inundation simulation model based on the United States Environmental Protection Agency Storm Water Management Model (SWMM) and a geographic information system (GIS)-based diffusive overland-flow model. SWMM is applied for computation of flows in storm sewer systems and flooding flows at junctions, while the GIS-based diffusive overland-flow model simulates surface runoff and inundation. One observed rainfall scenario on Haidian Island, Hainan Province, China was chosen to calibrate the model and the other two were used for validation. Comparisons of the model results with field-surveyed data and InfoWorks ICM (Integrated Catchment Modeling) modeled results indicated the inundation model in this paper can provide inundation extents and reasonable inundation depths even in a large study area.

Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

Abstract. The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

Studying the impact of construction dewatering discharges to the urban storm drainage network(s) of Doha city using infoworks integrated catchment modeling (ICM)

The discharge of construction dewatering flows to the storm drainage network for disposal is a common activity in Qatar. The Dupuit empirical approach was utilized to establish various hypothetical dewatering scenarios on the basis of site classifications, which were modeled on 4 Case Study Areas of Doha’s Existing Surface Drainage Network in order to study the impact of dewatering discharge against an established baseline. The simulations were undertaken using InfoWorks Integrated Catchment Modeling (ICM) software for critical and non-critical rainfall events. The results indicated significant localized flooding in excess of the baseline conditions for scenarios exceeding 0.5 m 3 /sec flows, while individual catchments demonstrated variations and sensitivities on the basis of catchment properties and rainfall events. It is evident that dewatering discharge under unpredictable rainfall events poses various levels of risk to the city’s infrastructure, which is further exacerbated due to the massive scale of construction activity in the country and the rising ground water table in Greater Doha Area basin.

Catchment‐scale sensitivity and uncertainty in water quality modelling

AbstractIn this paper, we assess the performance of the catchment model SIMulated CATchment model (SIMCAT), to predict nitrate and soluble reactive phosphorus concentrations against four monitoring regimes with different spatial and temporal sampling frequencies. The Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty framework is used, along with a general sensitivity analysis to understand relative parameter sensitivity. Improvements to model calibration are explored by introducing more detailed process representation using the Integrated Catchments model (INCA) water quality model, driven by the European hydrological predictions for the environment model. The results show how targeted sampling of headwater watercourses upstream of point discharges is essential for calibrating diffuse loads and can exert a strong influence on the whole‐catchment model performance. Further downstream, if the point discharges and loads are accurately represented, then the improvement in the catchment‐scale model performance is relatively small as more calibration points are added or frequency is increased.The higher‐order, dynamic model integrated catchments model of phosphorus dynamics, which incorporates sediment and biotic interaction, resulted in improved whole‐catchment performance over SIMCAT, although there are still large epistemic uncertainties from land‐phase export coefficients and runoff. However, the very large sampling errors in routine monitoring make it difficult to invest confidence in the modelling, especially because we know phosphorous transport to be very episodic and driven by high flow conditions for which there are few samples. The environmental modelling community seems to have been stuck in this position for some time, and whilst it is useful to use an uncertainty framework to highlight these issues, it has not widely been adopted, perhaps because there is no clear mechanism to allow uncertainties to influence investment decisions. This raises the question as to whether it might better place a cost on uncertainty and use this to drive more data collection or improved models, before making investment decisions concerning, for example, mitigation strategies. Copyright © 2016 John Wiley & Sons, Ltd.

Spatial and temporal variations of base cation release from chemical weathering on a hillslope scale

Cation release rates to catchment runoff from chemical weathering were assessed using an integrated catchment model that included the soil's unsaturated, saturated and riparian zones. In-situ mineral dissolution rates were calculated in these zones as a function of pH, aluminum and dissolved organic carbon (DOC) concentrations along a hillslope in Northern Sweden where soil water was monitored over nine years. Three independent sets of mineral dissolution equations of varying complexity were used: PROFILE, Transition-State Theory (TST), and the Palandri & Kharaka database.Normalization of the rate-coefficients was necessary to compare the equations, as published rate-coefficients gave base cation release rates differing by several orders of magnitude. After normalizing the TST- and Palandri & Kharaka-rate coefficients to match the base cation release rates calculated from the PROFILE-equations, calculated Ca2+ and Mg2+ release rates are consistent with mass balance calculations, whereas those of Na+ and K+ are overestimated. Our calculations further indicate that a significant proportion of base cations are released from the organic soils in the near-stream zone, in part due to its finer texture. Of the three sets of rate equations, the base cation release rates calculated from the normalized TST-equations were more variable than those calculated using the other two sets of equations, both spatially and temporally, due to its higher sensitivity to pH. In contrast, the normalized Palandri & Kharaka-equations were more sensitive to variations in soil temperature.

The INtegrated CAtchment model of phosphorus dynamics (INCA-P): Description and demonstration of new model structure and equations

INCA-P is a dynamic, catchment-scale phosphorus model which has been widely applied during the last decade. Since its original release in 2002, the model structure and equations have been significantly altered during several development phases. Here, we provide the first full model description since 2002 and then test the latest version of the model (v1.4.4) in a small rural catchment in northeast Scotland. The particulate phosphorus simulation was much improved compared to previous model versions, whilst the latest sorption equations allowed us to explore the potential time lags between reductions in terrestrial inputs and improvements in surface water quality, an issue of key policy relevance. The model is particularly suitable for use as a research tool, but should only be used to inform policy and land management in data-rich areas, where parameters and processes can be well-constrained. More long-term data is needed to parameterise dynamic models and test their predictions.

Urban stormwater forecasting model and drainage optimization based on water environmental capacity

Drainage systems in China are currently being transformed from combined sewer systems into separate sewer systems; newly built areas generally use the latter for sewage and stormwater treatment. Polluted stormwater runoff is discharged directly into rivers through pipelines, thereby deteriorating the water quality of rivers. In this work, an urban stormwater system model was built with Infoworks Integrated Catchment Modeling and validated by measured data. The loads at the pipe outlets during rainstorms were analyzed as well. Stormwater system was transformed by using mathematical models under the conditions of meeting river water quality standards and preventing damage to water environmental capacity. The relative errors of volume and peak runoff of model calibration were from −2.33 to +12.06 % and −13.43 to +8.7 %, respectively. The study indicates that the stormwater system model can be used in scenario analysis, and the stormwater system can accommodate floods over a recurring interval of 10 years. Moreover, stormwater can be directly discharged into water bodies without exceeding the carrying capacity of the water environment with the transformation of the stormwater system.

How can we reduce phosphorus export from lowland polders? Implications from a sensitivity analysis of a coupled model

Phosphorus (P) export from lowland polders has caused severe water pollution. Numerical models are an important resource that help water managers control P export. This study coupled three models, i.e., Phosphorus Dynamic model for Polders (PDP), Integrated Catchments model of Phosphorus dynamics (INCA-P) and Universal Soil Loss Equation (USLE), to describe the P dynamics in polders. Based on the coupled models and a dataset collected from Polder Jian in China, sensitivity analysis were carried out to analyze the cause-effect relationships between environmental factors and P export from Polder Jian. The sensitivity analysis results showed that P export from Polder Jian were strongly affected by air temperature, precipitation and fertilization. Proper fertilization management should be a strategic priority for reducing P export from Polder Jian. This study demonstrated the success of model coupling, and its application in investigating potential strategies to support pollution control in polder systems.

MIKE SHE modeling of ecohydrological processes: Merits, applications, and challenges

MIKE SHE is one of the most extensively used physically based distributed hydrological models that are capable of credibly interpreting the response mechanism of ecohydrological processes to ecosystem components and organization. However, implementing MIKE SHE in integrated catchment modeling is a complex task requiring an experienced modeling team with skills in a variety of disciplines, making it difficult for scientists without a background in hydrology or computer science to utilize this useful model. This review, from the perspective of ecology and environmental science, illustrates the important role of a physically based distributed model as a solution to issues related to ecohydrological processes, offering a major discussion of issues that received little attention from the previous reviewers and that would interest researchers without a hydrology background. The inevitable and possible difficulties confronting these potential users at the beginning and early stages of utilizing the model are also brought to light, with suggestions for solutions. This paper offers a brief review of MIKE SHE development and elaborates its main merits, key problems, and research on the model's theories and practices implemented by scholars. Lingering problems in current solutions are analyzed, and potential approaches to solutions are proposed. We hope that this paper provides some practical advice to researchers who want to initiate study of water issues related to modeling ecohydrological processes by employing MIKE SHE.

An INCA model for pathogens in rivers and catchments: Model structure, sensitivity analysis and application to the River Thames catchment, UK

Pathogens are an ongoing issue for catchment water management and quantifying their transport, loss and potential impacts at key locations, such as water abstractions for public supply and bathing sites, is an important aspect of catchment and coastal management. The Integrated Catchment Model (INCA) has been adapted to model the sources and sinks of pathogens and to capture the dominant dynamics and processes controlling pathogens in catchments. The model simulates the stores of pathogens in soils, sediments, rivers and groundwaters and can account for diffuse inputs of pathogens from agriculture, urban areas or atmospheric deposition. The model also allows for point source discharges from intensive livestock units or from sewage treatment works or any industrial input to river systems. Model equations are presented and the new pathogens model has been applied to the River Thames in order to assess total coliform (TC) responses under current and projected future land use. A Monte Carlo sensitivity analysis indicates that the input coliform estimates from agricultural sources and decay rates are the crucial parameters controlling pathogen behaviour. Whilst there are a number of uncertainties associated with the model that should be accounted for, INCA-Pathogens potentially provides a useful tool to inform policy decisions and manage pathogen loading in river systems.

Aquatic DOC export from subarctic Atlantic blanket bog in Norway is controlled by seasalt deposition, temperature and precipitation

Comprehensive and credible peatland carbon budgets, needed for global carbon accounting, must include lateral aquatic organic carbon export. Here, we quantify aquatic dissolved organic carbon (DOC) export for an Atlantic bog in subarctic Norway, the Andoya peatland, and test for sensitivity to climatic drivers. Hydrology, DOC concentrations and DOC export were simulated for 2000–2013 using the process-based catchment model Integrated Catchments model for Carbon (INCA-C), calibrated to site-specific water chemistry and hydrology (2011–2014) using readily-available data on temperature, precipitation and seasalt deposition. Measured streamwater DOC declined under seasalt episodes and was strongly positively related to temperature. Model calibrations successfully reproduced the water balance, variation in runoff (R2 = 0.67; Nash–Sutcliffe model efficiency NS = 0.67) and DOC concentrations (R2 = 0.85; NS = 0.84). The most sensitive model parameters related to temperature-sensitivity of DOC production and DOC (de)sorption sensitivity to seasalts. Model uncertainty related to parameter space was similar to interannual variation in DOC export. Mean annual modelled DOC export was 7.2 ± 0.7 g C m−2 year−1, roughly 35 % of the net land–atmospheric CO2 exchange at Andoya from 2009 to 2012 (estimated elsewhere). Current and antecedent mean temperature and precipitation were strong drivers of seasonal modelled DOC export, implying that warmer and wetter summers will lead to more DOC export. Evaluation of similar climate impacts on net peatland carbon accumulation requires additional exploration of the climate-sensitivity of land–atmosphere fluxes of CO2 and methane. Process-based models are valuable tools to account for lateral DOC exports in carbon balances of northern peatlands, especially where long-term monitoring data are lacking.

Assessment of contaminant fate in catchments using a novel integrated hydrobiogeochemical-multimedia fate model

Models for pollution exposure assessment typically adopt an overly simplistic representation of geography, climate and biogeochemical processes. This strategy is unsatisfactory when high temporal resolution simulations for sub-regional spatial domains are performed, in which parameters defining scenarios can vary interdependently in space and time. This is, for example, the case when assessing the influence of biogeochemical processing on contaminant fate. Here we present INCA-Contaminants, the Integrated Catchments model for Contaminants; a new model that simultaneously and realistically solves mass balances of water, carbon, sediments and contaminants in the soil-stream-sediment system of catchments and their river networks as a function of climate, land use/management and contaminant properties. When forced with realistic climate and contaminant input data, the model was able to predict polychlorinated biphenyls (PCBs) concentrations in multiple segments of a river network in a complex landscape. We analyzed model output sensitivity to a number of hydro-biogeochemical parameters. The rate of soil organic matter mineralization was the most sensitive parameter controlling PCBs levels in river water, supporting the hypothesis that organic matter turnover rates will influence re-mobilization of previously deposited PCBs which had accumulated in soil organic matrix. The model was also used to project the long term fate of PCB 101 under two climate scenarios. Catchment diffuse run-off and riverine transport were the major pathways of contaminant re-mobilization. Simulations show that during the next decade the investigated boreal catchment will shift from being a net atmospheric PCB sink to a net source for air and water, with future climate perturbation having little influence on this trend. Our results highlight the importance of using credible hydro-biogeochemical simulations when modeling the fate of hydrophobic contaminants.

FLOOD DAMAGE ASSESSMENT IN AGRICULTURAL AREA IN SELANGOR RIVER BASIN

Flooding is the major natural hazard that occurs in Malaysia. Flooding causes loss of lives, injuries, property damage and leave economic damage to the country, especially when it occurs in an agricultural area. There is still a lack of information available on floodplain especially on the impact of flooding in the agricultural area. This study focused on flooding and flooding impact in oil palm plantations, fruits and vegetables area. A river modeling is required to study the impact of flooding and to mitigate the floods using one mitigation option. A flood model was developed using InfoWorks Integrated Catchment Model (ICM) to carry out the analysis for flood damage assessment. With the aim of creating a flood damage map, Geographical Information System (GIS) was combined with the flood model to provide an ideal tool for the analysis of the flood damage and the effect of mitigation to flood damage. The estimated total damage for three different flood event; 10 ARI, 50 ARI and 100 ARI involved millions of ringgits. In order to reduce the flood impact along the Selangor River, a flood mitigation structure which is a retention pond was suggested, modeled and simulated. The effects of the retention ponds were analyzed and evaluated for 10 ARI, 50 ARI and 100 ARI. With this retention pond, flood extents of the flood events in agricultural area were shown capable of reduction significantly by 65.57% for 10 ARI, 76.18% for 50 ARI and 72.51% for 100 ARI.

An exploration of coupled surface–subsurface solute transport in a fully integrated catchment model

Summary Coupling surface and subsurface water flow in fully integrated hydrological codes is becoming common in hydrological research; however, the coupling of surface–subsurface solute transport has received much less attention. Previous studies on fully integrated solute transport focus on small scales, simple geometric domains, and have not utilised many different field data sources. The objective of this study is to demonstrate the inclusion of both flow and solute transport in a 3D, fully integrated catchment model, utilising high resolution observations of dissolved organic carbon (DOC) export from a wetland complex during a rainfall event. A sensitivity analysis is performed to span a range of transport conditions for the surface–subsurface boundary (e.g. advective exchange only, advection plus diffusion, advection plus full mechanical dispersion) and subsurface dispersivities. The catchment model captures some aspects of observed catchment behaviour (e.g. solute discharge at the catchment outlet, increasing discharge from wetlands with increased stream discharge, and counter-clockwise concentration–discharge relationships), although other known behaviours are not well represented in the model (e.g. slope of concentration–discharge plots). Including surface–subsurface solute transport aids in evaluating internal model processes, however there are challenges related to the influence of dispersion across the surface–subsurface interface, and non-uniqueness of the solute transport solution. This highlights that obtaining solute field data is especially important for constraining integrated models of solute transport.

Physically based modeling in catchment hydrology at 50: Survey and outlook

Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.