scholarly journals Comparative hydrology: relationships among physical characteristics, hydrological behavior, and results of the SWAT model in different regions of Brazil (Hidrologia comparativa: relações entre características físicas, comportamento hidrológico e ....)

2015 ◽  
Vol 7 (6) ◽  
pp. 1187
Author(s):  
Jorge Enoch Furquim Werneck Lima ◽  
Suzana Montenegro ◽  
Abelardo Antônio De Assunção Montenegro ◽  
Sergio Koide
Keyword(s):  
Land Use ◽  
Sensitivity Analysis ◽  
Model Calibration ◽  
Swat Model ◽  
Physical Characteristics ◽  
Model Parameters ◽  
Caatinga Biome ◽  
Comparative Hydrology ◽  
The Relationship ◽  
Semi Arid

Comparative hydrology studies, either by the similarities or the differences in the obtained data and results, represent an important tool for advancing knowledge of cause-effect relationships between the physical characteristics of the basins and their hydrological behavior. The objective of this study was to present a comparative analysis of measured and simulated characteristics of experimental and representative basins in different regions of Brazil. The SWAT model was used. Four catchments were evaluated: Alto Ipanema, located in the Caatinga biome, with semi-arid climate; Tapacurá, in the transition zone between the Caatinga and Atlantic Forest biomes, with hot and humid tropical climate; and Lago Descoberto and Alto Jardim, both in the Cerrado biome and with tropical altitude climate. The catchments were compared with respect to their physical characteristics (climate, soil, altitude, and land use). Using sensitivity analysis, it was found which of the SWAT model parameters best explain the hydrological behavior of the study regions. Considering its characteristics, the parameters values obtained in each catchment after model calibration were analyzed and compared, indicating the possibility of using these values as reference for their regions. The results indicate a clear relationship between the physical characteristics of watersheds, their respective hydrological behavior, and the values of two SWAT model parameters, CN2 and SOL_K. For other parameters, the relationship between the obtained values do not reflected adequately the characteristics of the catchment, indicating a need for improvement in the physical basis of the calibrated model.

scholarly journals Simulating the Hydrological Processes of a Meso-Scale Watershed on the Loess Plateau, China

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 878 ◽  
Author(s):  
Manman Leng ◽  
Yang Yu ◽  
Shengping Wang ◽  
Zhiqiang Zhang
Keyword(s):  
Land Use ◽  
Sensitivity Analysis ◽  
Loess Plateau ◽  
Swat Model ◽  
Hydrological Processes ◽  
P Value ◽  
Runoff Generation ◽  
The Loess Plateau ◽  
Monthly Streamflow ◽  
Meso Scale

The Soil and Water Assessment Tool (SWAT) model is widely used to simulate watershed streamflow by integrating complex interactions between climate, geography, soil, vegetation, land use/land cover and other human activities. Although there have been many studies involving sensitivity analysis, uncertainty fitting, and performance evaluation of SWAT model all over the world, identifying dominant parameters and confirming actual hydrological processes still remain essential for studying the effect of climate and land use change on the hydrological regime in some water-limited regions. We used hydro-climate and spatial geographical data of a watershed with an area of 3919 km2, located on the Loess Plateau of China, to explore the suitable criterion to select parameters for running the model, and to elucidate the dominant ones that govern the hydrological processes for achieving the sound streamflow simulation. Our sensitivity analysis results showed that parameters not passing the sensitive check (p-value < 0.05) could play a significant role in hydrological simulation rather than only the parameters with p-value lower than 0.05, indicating that the common protocol is not appropriate for selecting parameters by sensitivity screening only. Superior performance of the rarely used parameter SOL_BD was likely caused by a combination of lateral and vertical movement of water in the loess soils due to the run-on infiltration process that occurred for meso-scale watershed monthly streamflow modeling, contrasting with traditionally held infiltration excessive overland flow dominated runoff generation mechanisms that prevail on the Loess Plateau. Overall, the hydrological processes of meso-scale watershed in the region could be well simulated by the model though underestimates of monthly streamflow could occur. Simulated water balance results indicated that the evapotranspiration in the region was the main component leaving the watershed, accounting for 88.9% of annual precipitation. Surface runoff contributed to 63.2% of the streamflow, followed by lateral flow (36.6%) and groundwater (0.2%). Our research highlights the importance for selecting more appropriate parameters for distributed hydrological models, which could help modelers to better comprehend the meso-scale watershed runoff generation mechanism of the Loess Plateau and provide policy makers robust tool for developing sustainable watershed management planning in water-limited regions.

Sensitivity analysis and the challenges posed by multiple approaches: a multifaceted mess

2020 ◽  
Author(s):  
Monica Riva ◽  
Aronne Dell'Oca ◽  
Alberto Guadagnini
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Global Sensitivity Analysis ◽  
System Model ◽  
Model Parameters ◽  
Model Output ◽  
Multiple Model ◽  
Total Uncertainty ◽  
Global Sensitivity ◽  
Sensitivity Indices

&lt;p&gt;Modern models of environmental and industrial systems have reached a relatively high level of complexity. The latter aspect could hamper an unambiguous understanding of the functioning of a model, i.e., how it drives relationships and dependencies among inputs and outputs of interest. Sensitivity Analysis tools can be employed to examine this issue.&lt;/p&gt;&lt;p&gt;Global sensitivity analysis (GSA) approaches rest on the evaluation of sensitivity across the entire support within which system model parameters are supposed to vary. In this broad context, it is important to note that the definition of a sensitivity metric must be linked to the nature of the question(s) the GSA is meant to address. These include, for example: (i) which are the most important model parameters with respect to given model output(s)?; (ii) could we set some parameter(s) (thus assisting model calibration) at prescribed value(s) without significantly affecting model results?; (iii) at which space/time locations can one expect the highest sensitivity of model output(s) to model parameters and/or knowledge of which parameter(s) could be most beneficial for model calibration?&lt;/p&gt;&lt;p&gt;The variance-based Sobol&amp;#8217; Indices (e.g., Sobol, 2001) represent one of the most widespread GSA metrics, quantifying the average reduction in the variance of a model output stemming from knowledge of the input. Amongst other techniques, Dell&amp;#8217;Oca et al. [2017] proposed a moment-based GSA approach which enables one to quantify the influence of uncertain model parameters on the (statistical) moments of a target model output.&lt;/p&gt;&lt;p&gt;Here, we embed in these sensitivity indices the effect of uncertainties both in the system model conceptualization and in the ensuing model(s) parameters. The study is grounded on the observation that physical processes and natural systems within which they take place are complex, rendering target state variables amenable to multiple interpretations and mathematical descriptions. As such, predictions and uncertainty analyses based on a single model formulation can result in statistical bias and possible misrepresentation of the total uncertainty, thus justifying the assessment of multiple model system conceptualizations. We then introduce copula-based sensitivity metrics which allow characterizing the global (with respect to the input) value of the sensitivity and the degree of variability (across the whole range of the input values) of the sensitivity for each value that the prescribed model output can possibly undertake, as driven by a governing model. In this sense, such an approach to sensitivity is global with respect to model input(s) and local with respect to model output, thus enabling one to discriminate the relevance of an input across the entire range of values of the modeling goal of interest. The methodology is demonstrated in the context of flow and reactive transport scenarios.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Sobol, I. M., 2001. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math. Comput. Sim., 55, 271-280.&lt;/p&gt;&lt;p&gt;Dell&amp;#8217;Oca, A., Riva, M., Guadagnini, A., 2017. Moment-based metrics for global sensitivity analysis of hydrological systems. Hydr. Earth Syst. Sci., 21, 6219-6234.&lt;/p&gt;

Simulation of Nitrate Concentration Affected from Land Use Changes in the Lower Part of Yom River Basin,Thailand: A Preliminary Study

2014 ◽  
Vol 931-932 ◽  
pp. 738-743
Author(s):  
Satika Boonkaewwan ◽  
Srilert Chotpantarat
Keyword(s):  
Land Use ◽  
River Basin ◽  
Swat Model ◽  
Land Use Changes ◽  
Sediment Concentration ◽  
Model Parameters ◽  
The North ◽  
Optimal Values ◽  
Preliminary Study ◽  
Year 2000

The Lower Yom River Basin is located in the north of Thailand. This study carried out to calibrate and validate using SWAT model in terms of streamflow and sediment concentration hydrographs (Year 2000-2012) for 3 RID streamflow gauging stations (the Royal Irrigation Department). The nitrates concentrations simulate have been influenced of land use changes during last ten years. Optimal values of model parameters derived from calibration and validation processes, which showed well fitted between observed and simulated results. In the last decade, particular in Lower Yom River, the land use change gradually transformed to be more paddy field and has been increased 127.48 km2 (approx. 0.87% increase), followed by urban area, which has been increased 196.66 km2 (approx. 1.35% increase), respectively. Average monthly concentration of nitrate increased 38.28 mg/l (approx.13.40 % increase), 43.17 mg/l (approx.12.00% increase), 43.02 mg/l (approx. 8.60% increase) at station Y.6, Y.4 and Y.17, respectively. Accordingly, on the basis of the results presented in this study, land use changes can significantly affect on concentrations of nitrate.

scholarly journals Soil erosion and sediment delivery in a mountain catchment under scenarios of land use change using a spatially distributed numerical model

2012 ◽  
Vol 16 (5) ◽  
pp. 1321-1334 ◽  
Author(s):  
L. C. Alatorre ◽  
S. Beguería ◽  
N. Lana-Renault ◽  
A. Navas ◽  
J. M. García-Ruiz
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Sediment Yield ◽  
Model Calibration ◽  
Global Optimum ◽  
Model Parameters ◽  
Sediment Delivery ◽  
Yield Data ◽  
Good Convergence ◽  
Spatially Distributed

Abstract. Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are of great interest to assess the expected effect of LULC changes on soil erosion and sediment yield. However, they can only be applied if spatially distributed data is available for their calibration. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small (2.84 km2) experimental catchment in the Central Spanish Pyrenees. Model calibration was performed based on a dataset of soil redistribution rates derived from point 137Cs inventories, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space, which was not possible to attain if only external (not spatially distributed) sediment yield data were available. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios were then modeled to reproduce land use at the beginning of the twentieth century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr−1) and sediment delivery (11.2 to 1.2 Mg yr−1 ha−1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation recolonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

Sensitivity of Hydrological Model to Landscape Pattern Change

2013 ◽  
Vol 765-767 ◽  
pp. 3061-3065
Author(s):  
Chong Wei ◽  
Jie Chen ◽  
Xuan Song
Keyword(s):  
Land Use ◽  
Model Calibration ◽  
Hydrological Model ◽  
Spatial Configuration ◽  
Swat Model ◽  
Landscape Composition ◽  
Water Yield ◽  
Validation Period ◽  
Pattern Change ◽  
Spatial Configurations

The hydrological model is a tool to simulate the hydrological processes and to solve the practical problem. The composition and spatial configuration of landscape often result in variation of hydrological conditions. This study is applied to compare the results of SWAT model with different land use maps in Qihe watershed, and shows that the sensitivity of SWAT model to landscape spatial configurations at landscape level is weak, except the landscape composition. After model calibration, both models satisfy the observed data well, which means though the land use map beyond the real landscape spatial configurations, the SWAT model could also describe the water yield of Qihe watershed accurately during the validation period.

scholarly journals Calibração hidrológica do modelo SWAT em bacia hidrográfica caracterizada pela expansão do cultivo da cana-de-açúcar

2020 ◽  
Vol 13 (2) ◽  
pp. 576
Author(s):  
Letícia Lopes Martins ◽  
Wander Araújo Martins ◽  
Jener Fernando Leite De Moraes ◽  
Mário José Pedro Júnior ◽  
Isabella Clerici De Maria
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Model Calibration ◽  
Assessment Tool ◽  
Swat Model ◽  
Sao Paulo ◽  
São Paulo ◽  
Calibration And Validation ◽  
Water Assessment ◽  
Soil And Water

A dificuldade na gestão de recursos hídricos aliada à dinâmica do uso e ocupação do solo em bacias hidrográficas agrícolas são fatores relevantes para a conservação da água e solo. A gestão de bacias hidrográficas, bem como o monitoramento de cenários de expansão agrícola e mudança no uso do solo, podem se beneficiar de ferramentas de modelagem hidrossedimentológica, como o SWAT (Soil and Water Assessment Tool). Entretanto, para que os resultados obtidos sejam confiáveis, os modelos precisam ser calibrados. Objetivou-se, neste trabalho, calibrar e validar o modelo SWAT, para a variável vazão, tendo como base a bacia hidrográfica do Ribeirão do Pinhal, Limeira -São Paulo, que se caracteriza pela expansão da cana-de-açúcar sobre áreas citrícolas. Dados de vazão de um posto fluviométrico localizado no exutório da bacia foram utilizados para a calibração e validação, a partir de séries temporais diferentes.  Utilizou-se o software QSWAT para a simulação hidrológica e o SWAT-CUP para a calibração e validação do modelo. O modelo foi calibrado e validado resultando nos seguintes índices estatísticos NSE=0,64; PBIAS=15,2 e RSR=0,60 para calibração e NSE=0,68 PBIAS=-2,8 e RSR=0,56 para a validação. O ajuste de parâmetros do SWAT (USLE_P, USLE_C, CN2) e do calendário de operações da cana-de-açúcar em acordo com a situação real da bacia foi necessário para a calibração do modelo. Os resultados indicam que o modelo SWAT subestima as vazões extremas, no entanto, dentro de faixa aceitável. O SWAT, após a calibração, pode ser utilizado na gestão de recursos hídricos na bacia do Ribeirão do Pinhal.Hydrological calibration of the SWAT model in a watershed characterized by the expansion of sugarcane cultivationA B S T R A C TThe difficulty in water resources management combined with the dynamics of land use and occupation in agricultural watersheds are relevant factors for water and soil conservation. River basin management, as well as monitoring scenarios of agricultural expansion and land-use change, can benefit from hydrossedimentological modeling tools such as the SWAT (Soil and Water Assessment Tool). However, for the results to be reliable, the models must be calibrated. The objective of this study was to calibrate and validate the SWAT model for the flow variable, based on the Ribeirão do Pinhal watershed, Limeira-São Paulo, which is characterized by the expansion of sugarcane over citrus areas. Flow data from a fluviometric station located in the basin's outfall were used for calibration and validation from different time series. QSWAT software was used for hydrological simulation and SWAT-CUP for model calibration and validation. The model was calibrated and validated resulting in the following statistical indices NSE = 0.64; PBIAS = 15.2 and RSR = 0.60 for calibration and NSE = 0.68 PBIAS = -2.8 and RSR = 0.56 for validation. Adjustment of SWAT parameters (USLE_P, USLE_C, and CN2) and the sugarcane operation schedule according to the actual basin situation was necessary for model calibration. The results indicate that the SWAT model underestimates the extreme flow rates, however, within an acceptable range. After calibration, the SWAT can be used to manage water resources in the Ribeirão do Pinhal basin.Keywords: Hydrologic simulation; land use; flow rate.

scholarly journals Estimating Ectopic Beat Probability with Simplified Statistical Models that Account for Experimental Uncertainty

2021 ◽  
Author(s):  
Qingchu Jin ◽  
Joseph L. Greenstein ◽  
Raimond L. Winslow
Keyword(s):  
Sensitivity Analysis ◽  
Cardiac Myocyte ◽  
Special Property ◽  
Biophysical Model ◽  
Ectopic Beat ◽  
Model Parameters ◽  
Computational Burden ◽  
Simplified Approach ◽  
Ectopic Beats ◽  
The Relationship

AbstractEctopic beats (EBs) are cellular arrhythmias that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. Here, we develop a simplified approach in which logistic regression models (LRMs) are used to define a mapping between the parameters of complex cell models and the probability of EBs (P(EB)). As an example, in this study, we build an LRM for P(EB) as a function of diastolic cytosolic Ca2+ concentration ([Ca2+]i), sarcoplasmic reticulum (SR) Ca2+ load, and kinetic parameters of the inward rectifier K+ current (IK1) and ryanodine receptor (RyR). This approach, which we refer to as arrhythmia sensitivity analysis, allows for evaluation of the relationship between these arrhythmic event probabilities and their associated parameters. This LRM is also used to demonstrate how uncertainties in experimentally measured values determine the uncertainty in P(EB). In a study of the role of [Ca2+]SR uncertainty, we show a special property of the uncertainty in P(EB), where with increasing [Ca2+]SR uncertainty, P(EB) uncertainty first increases and then decreases. Lastly, we demonstrate that IK1 suppression, at the level that occurs in heart failure myocytes, increases P(EB).Author summaryAn ectopic beat is an abnormal cellular electrical event which can trigger dangerous arrhythmias in the heart. Complex biophysical models of the cardiac myocyte can be used to reveal how cell properties affect the probability of ectopic beats. However, such analyses can pose a huge computational burden. We develop a simplified approach that enables a highly complex biophysical model to be reduced to a rather simple statistical model from which the functional relationship between myocyte model parameters and the probability of an ectopic beat is determined. We refer to this approach as arrhythmia sensitivity analysis. Given the efficiency of our approach, we also use it to demonstrate how uncertainties in experimentally measured myocyte model parameters determine the uncertainty in ectopic beat probability. We find that, with increasing model parameter uncertainty, the uncertainty in probability of ectopic beat first increases and then decreases. In general, our approach can efficiently analyze the relationship between cardiac myocyte parameters and the probability of ectopic beats and can be used to study how uncertainty of these cardiac myocyte parameters influences the ectopic beat probability.

scholarly journals Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

2008 ◽  
Vol 32 (4) ◽  
pp. 1699-1712 ◽  
Author(s):  
Ivan Luiz Zilli Bacic ◽  
David G. Rossiter ◽  
Christiaan Mathias Mannaerts
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Management Practices ◽  
Expert Knowledge ◽  
Stream Water ◽  
Model Parameters ◽  
Calibration Data ◽  
Santa Catarina ◽  
Environmental Models ◽  
Santa Catarina State

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Systematic evaluation of biofilm models for engineering practice: components and critical assumptions

2011 ◽  
Vol 64 (4) ◽  
pp. 930-944 ◽  
Author(s):  
J. P. Boltz ◽  
E. Morgenroth ◽  
D. Brockmann ◽  
C. Bott ◽  
W. J. Gellner ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Biofilm Reactor ◽  
Systematic Evaluation ◽  
Engineering Practice ◽  
Model Parameters ◽  
Concentration Gradients ◽  
Reactor Model ◽  
Biofilm Model ◽  
Calibration Protocol

Biofilm models are valuable tools for the design and evaluation of biofilm-based processes despite several uncertainties including the dynamics and rate of biofilm detachment, concentration gradients external to the biofilm surface, and undefined biofilm reactor model calibration protocol. The present investigation serves to (1) systematically evaluate critical biofilm model assumptions and components and (2) conduct a sensitivity analysis with the aim of identifying parameter subsets for biofilm reactor model calibration. AQUASIM was used to describe submerged-completely mixed combined carbon oxidation and nitrification IFAS and MBBR systems, and tertiary nitrification and denitrification MBBRs. The influence of uncertainties in model parameters on relevant model outputs was determined for simulated scenarios by means of a local sensitivity analysis. To obtain reasonable simulation results for partially penetrated biofilms that accumulated a substantial thickness in the modelled biofilm reactor (e.g. 1,000 μm), an appropriate biofilm discretization was applied to properly model soluble substrate concentration gradients and, consistent with the assumed mechanism for describing biofilm biomass distribution, biofilm biomass spatial variability. The MTBL thickness had a significant impact on model results for each of the modelled reactor configurations. Further research is needed to develop a mathematical description (empirical or otherwise) of the MTBL thickness that is relevant to modern biofilm reactors. No simple recommendations for a generally applicable calibration protocol are provided, but sensitivity analysis has been proven to be a powerful tool for the identification of highly sensitive parameter subsets for biofilm (reactor) model calibration.

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