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Hydrological model

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1367: 111: 79: 736: 39: 367:"Application of machine learning techniques for rainfall-runoff modelling" by Solomatine and Siek (2004), and "Data-driven modelling approaches for hydrological forecasting and prediction" by Valipour et al. (2021). These models are commonly used for predicting rainfall, runoff, groundwater levels, and water quality, and have proven to be valuable tools for optimizing water resource management strategies. 376: 666: 363:
data-driven models leverage techniques from artificial intelligence, machine learning, and statistical analysis, including correlation analysis, time series analysis, and statistical moments, to learn complex patterns and dependencies from historical data. This allows them to make more accurate predictions and provide insights into the underlying processes.
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Scale models commonly use physical properties that are similar to their natural counterparts (e.g., gravity, temperature). Yet, maintaining some properties at their natural values can lead to erroneous predictions. Properties such as viscosity, friction, and surface area must be adjusted to maintain
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are a mathematical technique for determine the probability of a state or event based on a previous state or event. The event must be dependent, such as rainy weather. Markov Chains were first used to model rainfall event length in days in 1976, and continues to be used for flood risk assessment and
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is a mathematical operation on two different functions to produce a third function. With respect to hydrologic modeling, convolution can be used to analyze stream discharge's relationship to precipitation. Convolution is used to predict discharge downstream after a precipitation event. This type of
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Groundwater flow can be visualized using a scale model built of acrylic and filled with sand, silt, and clay. Water and tracer dye may be pumped through this system to represent the flow of the simulated groundwater. Some physical aquifer models are between two and three dimensions, with simplified
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Specialized software may also be used to solve sets of equations using a graphical user interface and complex code, such that the solutions are obtained relatively rapidly and the program may be operated by a layperson or an end user without a deep knowledge of the system. There are model software
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Scale models offer a useful approximation of physical or chemical processes at a size that allows for greater ease of visualization. The model may be created in one (core, column), two (plan, profile), or three dimensions, and can be designed to represent a variety of specific initial and boundary
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as boxes with arrows pointing toward a box that represents the main river. The conceptual model would then specify the important watershed features (e.g., land use, land cover, soils, subsoils, geology, wetlands, lakes), atmospheric exchanges (e.g., precipitation, evapotranspiration), human uses
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analysis is used to characterize temporal correlation within a data series as well as between different time series. Many hydrologic phenomena are studied within the context of historical probability. Within a temporal dataset, event frequencies, trends, and comparisons may be made by using the
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Since their inception in the latter half of the 20th century, data-driven models have gained popularity in the water domain, as they help improve forecasting, decision-making, and management of water resources. A couple of notable publications that use data-driven models in hydrology include
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in hydrology emerged as an alternative approach to traditional statistical models, offering a more flexible and adaptable methodology for analysing and predicting various aspects of hydrological processes. While statistical models rely on rigorous assumptions about probability distributions,
434:(e.g., agricultural, municipal, industrial, navigation, thermo- and hydro-electric power generation), flow processes (e.g., overland, interflow, baseflow, channel flow), transport processes (e.g., sediments, nutrients, pathogens), and events (e.g., low-, flood-, and mean-flow conditions). 1378:
to characterize the unique aspects of the system being studied. These parameters can be obtained using laboratory and field studies, or estimated by finding the best correspondence between observed and modelled behavior. Between neighbouring catchments which have physical and hydrological
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are used to mathematically define the behavior of the system. Algebraic equations are likely often used for simple systems, while ordinary and partial differential equations are often used for problems that change in space in time. Examples of governing equations include:
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An early process analog model was an electrical network model of an aquifer composed of resistors in a grid. Voltages were assigned along the outer boundary, and then measured within the domain. Electrical conductivity paper can also be used instead of resistors.
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of interest, and are often constructed using entities (stores of water) and relationships between these entitites (flows or fluxes between stores). The conceptual model is coupled with scenarios to describe specific events (either input or outcome scenarios).
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is a simplification of a real-world system (e.g., surface water, soil water, wetland, groundwater, estuary) that aids in understanding, predicting, and managing water resources. Both the flow and quality of water are commonly studied using hydrologic models.
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Many real-world mathematical models are too complex to meet the simplifying assumptions required for an analytic solution. In these cases, the modeler develops a numerical solution that approximates the exact solution. Solution techniques include the
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The frequency of extremal events, such as severe droughts and storms, often requires the use of distributions that focus on the tail of the distribution, rather than the data nearest the mean. These techniques, collectively known as
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The model combines continuity and storage-discharge equations, which yields an ordinary differential equation that describes outflow from each reservoir. The continuity equation for tank models is:
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statistical techniques of time series analysis. The questions that are answered through these techniques are often important for municipal planning, civil engineering, and risk assessments.
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diagrams are the most commonly used statistical regression model in the physical sciences, but there are a variety of models available from simplistic to complex. In a bivariate diagram, a
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Abrahart, R. P., See, L. M., & Solomatine, D. P. (2008). Practical Hydroinformatics: Computational Intelligence and Technological Developments in Water Applications. Springer.
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Solomatine, D. P., & Siek, M. B. (2004). Application of machine learning techniques for rainfall-runoff modeling. Hydroinformatics: A wide range of technologies, 333-342.
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Valipour, M., Shahsavani, D., & Choubin, B. (2021). Data-driven modeling approaches for hydrological forecasting and prediction. Journal of Hydrology, 597, 125996.
390:. The conceptual model is used as the starting point for defining the important model components. The relationships between model components are then specified using 2089:
Ouarda, Taha B. M. J.; Girard, Claude; Cavadias, George S.; Bobée, Bernard (2001-12-10). "Regional flood frequency estimation with canonical correlation analysis".
453:(or Nash model) is widely used for rainfall-runoff analysis. The model uses a cascade of linear reservoirs along with a constant first-order storage coefficient, 2877: 337:
model would be considered a “lag convolution”, because of the predicting of the “lag time” as water moves through the watershed using this method of modeling.
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Marshall, R.J. (1980). "The estimation and distribution of storm movement and storm structure, using a correlation analysis technique and rain-gauge data".
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Ribeiro-Corréa, J.; Cavadias, G.S.; Clément, B.; Rousselle, J. (1995). "Identification of hydrological neighborhoods using canonical correlation analysis".
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Model scope and complexity is dependent on modeling objectives, with greater detail required if human or environmental systems are subject to greater risk.
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Zaharia, L. "L-MOMENTS AND THEIR USE IN MAXIMUM DISCHARGES'ANALYSIS IN CURVATURE CARPATHIANS REGION." Aerul si Apa. Componente ale Mediului (2013): 119.
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Exact solutions for algebraic, differential, and integral equations can often be found using specified boundary conditions and simplifying assumptions.
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is used to determine the ability of the calibrated model to meet the needs of the modeler. A commonly used measure of hydrologic model fit is the
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is a constant that indicates how quickly the reservoir drains; a smaller value indicates more rapid outflow. Combining these two equation yields
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that are commonly used in hydrology to describe data, as well as relationships between data. Using statistical methods, hydrologists develop
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that use equations to describe, predict, and manage hydrologic systems, analog models use non-mathematical approaches to simulate hydrology.
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Larocque, M. (1998). "Contribution of correlation and spectral analyses to the regional study of a large karst aquifer (Charente, France)".
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which indicates that the change in storage over time is the difference between inflows and outflows. The storage-discharge relationship is:
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Wallis, James R. (1965-12-01). "Multivariate statistical methods in hydrology—A comparison using data of known functional relationship".
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is an algebraic equation that predicts stream velocity as a function of channel roughness, the hydraulic radius, and the channel slope:
1605: 298:. These techniques may be used in the identification of flood dynamics, storm characterization, and groundwater flow in karst systems. 941: 1525:
Lee, S.S.; Kim, J.S.; Kim, D.J. (2001). "Monitoring of drawdown pattern during pumping in an unconfined physical aquifer model".
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describes solute movement in steady, one-dimensional flow using the solute dispersion coefficient and the groundwater velocity:
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Hamed, Khaled H. (2008-02-01). "Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis".
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Bobee, B.; Perreault, L.; Ashkar, F. (1993-03-01). "Two kinds of moment ratio diagrams and their applications in hydrology".
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packages for hundreds of hydrologic purposes, such as surface water flow, nutrient transport and fate, and groundwater flow.
242:) are used to describe the information content of data. These moments can then be used to determine an appropriate frequency 3360: 3406: 305: 749: 2925: 2194:
Nathan, R. J.; McMahon, T. A. (1990-07-01). "Evaluation of automated techniques for base flow and recession analyses".
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describes steady, one-dimensional groundwater flow using the hydraulic conductivity and the hydraulic gradient:
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Vargo, Erik; Pasupathy, Raghu; Leemis, Lawrence M. (2017-01-01). Glen, Andrew G.; Leemis, Lawrence M. (eds.).
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describes time-varying, multidimensional groundwater flow using the aquifer transmissivity and storativity:
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between observed variables, find trends in historical data, or forecast probable storm or drought events.
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similarities, the model parameters varies smoothly suggesting the spatial transferability of parameters.
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Nepal, Santosh; FlĂĽgel, Wolfgang-Albert; Krause, Peter; Fink, Manfred; Fischer, Christian (2017-07-30).
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Helsel, Dennis R., and Robert M. Hirsch. Statistical methods in water resources. Vol. 49. Elsevier, 1992
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Archibald, J.A.; Buchanan, B.P.; Fuka, D.R.; Georgakakos, C.B.; Lyon, S.W.; Walter, M.T. (2014-07-01).
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MODFLOW, a computational groundwater flow model based on methods developed by the US Geological Survey.
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transform methods are widely used to find analytic solutions to differential and integral equations.
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can be used for building conceptual models that are then populated using mathematical relationships.
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appropriate flow and transport behavior. This usually involves matching dimensionless ratios (e.g.,
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Experimental design of physical aquifer models for evaluation of groundwater remediation strategies
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that use comparable physics (e.g., electricity, heat, diffusion) to mimic the system of interest.
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Haan, C. T.; Allen, D. M.; Street, J. O. (1976-06-01). "A Markov Chain Model of daily rainfall".
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Matalas, N. C.; Reiher, Barbara J. (1967-03-01). "Some comments on the use of factor analyses".
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Salas, Jose D. Applied modeling of hydrologic time series. Water Resources Publication, 1980.
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Process analogs are used in hydrology to represent fluid flow using the similarity between
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Beven, Keith (1989). "Changing ideas in hydrology – The case of physically-based models".
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The degree and nature of correlation may be quantified, by using a method such as the
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Sharma, T. C. (1998-03-30). "An analysis of non-normal Markovian extremal droughts".
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statistical procedures used to identify relationships between hydrologic variables.
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Enemark, Trine; Peeters, Luk J.M.; Mallants, Dirk; Batelaan, Okke (February 2019).
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Conceptual models are commonly used to represent the important components (e.g.,
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The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science
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Geological Survey (U.S.) (1950-01-01). "Geological Survey water-supply paper".
1286:{\displaystyle f(a)={\frac {1}{2\pi i}}\oint _{\gamma }{\frac {f(z)}{z-a}}\,dz} 128: 2575: 2363: 1818: 1793: 1454: 1429: 3395: 3329: 3237: 3070: 2973: 2948: 2834: 2777: 2720: 2673: 2624: 2439: 2332: 2281: 2223: 2075: 2026: 1997:(1986-08-01). "Stochastic subsurface hydrology from theory to applications". 1921: 1870: 1675: 1463: 168: 140: 104: 2431: 2324: 2215: 2041: 2018: 1914:
10.1002/(sici)1099-1085(19980330)12:4<597::aid-hyp596>3.0.co;2-n
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PEEL, MURRAY C.; WANG, Q. J.; VOGEL, RICHARD M.; McMAHON, THOMAS A. (2001).
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Gupta, Hoshin Vijai; Sorooshian, Soroosh; Yapo, Patrice Ogou (1998-04-01).
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is used in hydrology to determine whether a relationship may exist between
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The Nash Model uses a cascade of linear reservoirs to predict streamflow.
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Instead of using a series of linear reservoirs, also the model of a
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http://drought.unl.edu/MonitoringTools/DownloadableSPIProgram.aspx
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Musyoka, F.K; Strauss, P; Zhao, G; Srinivasan, R; Klik, A (2021).
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Katz, Richard W; Parlange, Marc B; Naveau, Philippe (2002-08-01).
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Observed and modelled runoff using the non-linear reservoir model.
735: 38: 3101: 2507:"Hydrogeological conceptual model building and testing: A review" 1343: 387: 160: 159:, respectively. The corresponding analogs to fluid potential are 156: 51:
Prior to the advent of computer models, hydrologic modeling used
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describes laminar, steady, one-dimensional fluid flow using the
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The reaction factor Alpha increases with increasing discharge.
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Knighton, James; Singh, Kanishka; Evaristo, Jaivime (2020).
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is an integral method for solving boundary value problems:
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For example, a watershed model could be represented using
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that use miniaturized versions of the physical system and
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JAWRA Journal of the American Water Resources Association
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Non-linear reservoir model for rainfall-runoff relations
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A non-linear reservoir used in rainfall-runoff modelling
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boundary conditions simulated using pumps and barriers.
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Rainfall-runoff modelling using a non-linear reservoir
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Two general categories of analog models are common;
2039: 1361: 1974:https://water.usgs.gov/osw/bulletin17b/dl_flow.pdf 1934: 1285: 1180: 1101: 989: 921: 868: 724: 651: 589: 531: 2885: 2687:Archibald, Josephine A.; Walter, M. Todd (2014). 316:or higher-order model may be fitted to the data. 3393: 2482:Environmental and Hydrological Systems Modelling 2686: 2409: 1636:. HYDROLOGIC ENGINEERING CENTER DAVIS CA, 1962. 759:in the above equation, that may also be called 55:to simulate flow and transport systems. Unlike 1569:https://books.google.com/books?isbn=0124200788 770:In the left figure the relation is quadratic: 763:, needs to be replaced by another symbol, say 3150: 2871: 2302: 2193: 1567:Principles of Soil and Plant Water Relations 114:A two-dimensional scale model of an aquifer. 2479: 869:{\displaystyle v={k \over n}R^{2/3}S^{1/2}} 95:conditions as needed to answer a question. 3157: 3143: 2878: 2864: 532:{\displaystyle {dS(t) \over dt}=i(t)-q(t)} 3109:: Saltmod coupled to a groundwater model 2824: 2767: 2663: 2614: 2604: 2560: 2558: 2538: 2065: 1817: 1758: 1524: 1453: 1276: 3164: 2236: 2158: 1365: 734: 664: 374: 109: 77: 37: 2345: 1728:Probability and statistics in hydrology 1338:Commonly used numerical models include 273: 27:Predicting and managing water resources 14: 3394: 3325:Construction and management simulation 2644:Journal of Hydrology: Regional Studies 2555: 1993: 1891: 1751:Computational Probability Applications 1645: 1604:: CS1 maint: archived copy as title ( 1296: 789: 3138: 2859: 1937:"Statistics of extremes in hydrology" 1688: 1476: 1427: 1388:Nash-Sutcliffe efficiency coefficient 922:{\displaystyle {\vec {q}}=-K\nabla h} 354: 198: 3361:List of computer simulation software 2274:Geological Survey Water-supply Paper 370: 143:. The analogs to fluid flow are the 1843:Stochastic Hydrology and Hydraulics 1301: 386:represent hydrologic systems using 306:independent and dependent variables 24: 2387:"Markov Chains explained visually" 1317: 1169: 1161: 1140: 1132: 1090: 1082: 1067: 1059: 1034: 1020: 978: 970: 949: 913: 652:{\displaystyle K{dq \over dt}=i-q} 122: 25: 3418: 2844: 1620:"Conductive Paper and Pen: PASCO" 406:. The model is then solved using 2926:Irrigation environmental impacts 1634:Statistical methods in hydrology 1362:Model calibration and evaluation 73: 46: 3289:Integrated assessment modelling 2792: 2735: 2680: 2631: 2580: 2569: 2498: 2473: 2464: 2455: 2446: 2403: 2379: 2370: 2339: 2296: 2265: 2230: 2187: 2152: 2117: 2082: 2033: 1987: 1978: 1967: 1928: 1885: 1834: 1785: 1742: 1733: 1717: 1682: 725:{\displaystyle q=i(1-e^{-t/k})} 419:features, events, and processes 280:Pearson correlation coefficient 1639: 1626: 1612: 1573: 1561: 1518: 1505: 1470: 1421: 1410:Soil and Water Assessment Tool 1259: 1253: 1213: 1207: 898: 719: 689: 576: 570: 561: 555: 526: 520: 511: 505: 485: 479: 400:partial differential equations 246:, which can then be used as a 13: 1: 2959:Drainage system (agriculture) 2886:Agricultural water management 2531:10.1016/j.jhydrol.2018.12.007 2259:10.1016/S0022-1694(97)00155-8 2111:10.1016/S0022-1694(01)00488-7 1961:10.1016/S0309-1708(02)00056-8 1798:Hydrological Sciences Journal 1711:10.1016/j.jhydrol.2007.11.009 1415: 1001:Advection-Dispersion equation 755:In such a model the constant 84:Mississippi River Basin Model 3258:Hydrological transport model 3212:Protein structure prediction 3207:Modelling biological systems 3002:Hydrological transport model 2748:Geophysical Research Letters 2181:10.1016/0022-1694(80)90063-3 2146:10.1016/0022-1694(95)02719-6 1769:10.1007/978-3-319-43317-2_12 1499:10.1016/0022-1694(89)90101-7 1331:methods, among many others. 324:principal component analysis 7: 3202:Metabolic network modelling 2480:Jayawardena, A. W. (2014). 1941:Advances in Water Resources 1393: 590:{\displaystyle q(t)=S(t)/K} 10: 3423: 3407:Water resources management 3315:Business process modelling 3030:Groundwater energy balance 2665:10.1016/j.ejrh.2014.06.003 217: 88:US Army Corps of Engineers 3348: 3302: 3276: 3220: 3187:Chemical process modeling 3172: 3116: 3080:Agro-hydro-salinity group 3079: 3053: 3015: 2982: 2934: 2891: 2364:10.1080/14786440109462720 1819:10.1080/02626660109492806 1455:10.5194/hess-16-3075-2012 1400:Hydrological optimization 933:Groundwater flow equation 268:generalized extreme value 3233:Chemical transport model 3197:Infectious disease model 3107:SahysMod polygonal model 3102:SaltMod integrated model 3007:Runoff model (reservoir) 2412:Water Resources Research 2305:Water Resources Research 2196:Water Resources Research 2046:Water Resources Research 1999:Water Resources Research 1648:Water Resources Research 1515:(Doctoral dissertation). 1428:Rodhe, A. (2012-09-03). 3087:Hydrology (agriculture) 2432:10.1029/WR012i003p00443 2325:10.1029/WR003i001p00213 2216:10.1029/WR026i007p01465 2019:10.1029/WR022i09Sp0135S 1668:10.1029/WR001i004p00447 1434:Hydrol. Earth Syst. Sci 212:empirical relationships 181:electrical conductivity 3040:Hydraulic conductivity 2805:Hydrological Processes 1894:Hydrological Processes 1527:Hydrological Processes 1511:Humphrey, M.D., 1992. 1371: 1287: 1182: 1103: 991: 923: 870: 740: 726: 670: 662:and has the solution: 653: 591: 533: 451:linear-reservoir model 380: 256:extreme value analysis 177:hydraulic conductivity 115: 91: 43: 18:Hydrological modelling 3366:Mathematical modeling 3310:Biopsychosocial model 3097:Leaching model (soil) 3092:Soil salinity control 2921:Irrigation management 2916:Irrigation statistics 1369: 1288: 1183: 1104: 992: 924: 871: 738: 727: 668: 654: 592: 534: 378: 189:diffusion coefficient 113: 81: 41: 3320:Catastrophe modeling 3166:Scientific modelling 2984:Surface water/runoff 2769:10.1029/2019GL085937 2754:(1): e2019GL085937. 2511:Journal of Hydrology 2239:Journal of Hydrology 2161:Journal of Hydrology 2126:Journal of Hydrology 2091:Journal of Hydrology 1691:Journal of Hydrology 1479:Journal of Hydrology 1405:Scientific modelling 1374:Physical models use 1201: 1126: 1010: 942: 889: 811: 750:non-linear reservoir 677: 611: 549: 467: 274:Correlation analysis 185:thermal conductivity 3263:Modular Ocean Model 3061:Acid sulphate soils 2936:Subsurface drainage 2817:2017HyPr...31.2812N 2760:2020GeoRL..4785937K 2705:2014JAWRA..50..497A 2656:2014JHyRS...1...74A 2523:2019JHyd..569..310E 2424:1976WRR....12..443H 2346:Pearson, K (1901). 2317:1967WRR.....3..213M 2251:1998JHyd..205..217L 2208:1990WRR....26.1465N 2173:1980JHyd...48...19M 2138:1995JHyd..173...71R 2103:2001JHyd..254..157O 2058:1998WRR....34..751G 2011:1986WRR....22R.135G 1953:2002AdWR...25.1287K 1947:(8–12): 1287–1304. 1906:1998HyPr...12..597S 1855:1993SHH.....7...41B 1810:2001HydSJ..46..147P 1703:2008JHyd..349..350H 1660:1965WRR.....1..447W 1539:2001HyPr...15..479L 1491:1989JHyd..105..157B 1446:2012HESS...16.3075R 1297:Solution algorithms 795:Governing equations 790:Governing equations 392:algebraic equations 302:Regression analysis 57:mathematical models 3356:Data visualization 3340:Input–output model 3253:Hydrological model 3243:Geologic modelling 2997:Hydrological model 2964:Watertable control 2901:Surface irrigation 2713:10.1111/jawr.12137 2391:Explained Visually 1863:10.1007/BF01581566 1372: 1283: 1178: 1099: 987: 919: 866: 802:Manning's equation 741: 722: 671: 649: 587: 529: 404:integral equations 381: 360:Data-driven models 355:Data-driven models 232:standard deviation 208:mathematical model 204:Statistical models 199:Statistical models 175:). The analogs to 173:chemical potential 116: 92: 44: 3389: 3388: 3268:Wildfire modeling 3248:Groundwater model 3228:Atmospheric model 3132: 3131: 3035:Groundwater model 2992:Contour trenching 2974:Drainage by wells 2969:Drainage research 2954:Drainage equation 2826:10.1002/hyp.11199 2811:(16): 2812–2826. 2606:10.3390/w13162238 2491:978-0-415-46532-8 2484:. US: CRC Press. 2067:10.1029/97WR03495 2005:(9S): 135S–145S. 1724:Yevjevich, Vujica 1325:finite-difference 1274: 1235: 1192:Cauchy's integral 1176: 1147: 1097: 1074: 1048: 985: 901: 828: 635: 497: 388:physical concepts 384:Conceptual models 371:Conceptual models 296:residual analysis 248:probability model 187:, and the solute 16:(Redirected from 3414: 3402:Hydrology models 3381:Visual analytics 3376:Systems thinking 3294:Population model 3159: 3152: 3145: 3136: 3135: 3025:Groundwater flow 2911:Tidal irrigation 2880: 2873: 2866: 2857: 2856: 2839: 2838: 2828: 2796: 2790: 2789: 2771: 2739: 2733: 2732: 2684: 2678: 2677: 2667: 2635: 2629: 2628: 2618: 2608: 2584: 2578: 2573: 2567: 2562: 2553: 2552: 2542: 2502: 2496: 2495: 2477: 2471: 2468: 2462: 2459: 2453: 2450: 2444: 2443: 2407: 2401: 2400: 2398: 2397: 2383: 2377: 2374: 2368: 2367: 2343: 2337: 2336: 2300: 2294: 2293: 2269: 2263: 2262: 2245:(3–4): 217–231. 2234: 2228: 2227: 2202:(7): 1465–1473. 2191: 2185: 2184: 2156: 2150: 2149: 2121: 2115: 2114: 2097:(1–4): 157–173. 2086: 2080: 2079: 2069: 2037: 2031: 2030: 1991: 1985: 1982: 1976: 1971: 1965: 1964: 1932: 1926: 1925: 1889: 1883: 1882: 1838: 1832: 1831: 1821: 1789: 1783: 1782: 1762: 1746: 1740: 1737: 1731: 1721: 1715: 1714: 1697:(3–4): 350–363. 1686: 1680: 1679: 1643: 1637: 1630: 1624: 1623: 1616: 1610: 1609: 1603: 1595: 1593: 1592: 1583:. Archived from 1577: 1571: 1565: 1559: 1558: 1522: 1516: 1509: 1503: 1502: 1485:(1–2): 157–172. 1474: 1468: 1467: 1457: 1440:(9): 3075–3082. 1425: 1302:Analytic methods 1292: 1290: 1289: 1284: 1275: 1273: 1262: 1248: 1246: 1245: 1236: 1234: 1220: 1187: 1185: 1184: 1179: 1177: 1175: 1167: 1159: 1148: 1146: 1138: 1130: 1113:Poiseuille's law 1108: 1106: 1105: 1100: 1098: 1096: 1088: 1080: 1075: 1073: 1065: 1057: 1049: 1047: 1046: 1045: 1032: 1028: 1027: 1017: 996: 994: 993: 988: 986: 984: 976: 968: 957: 956: 928: 926: 925: 920: 903: 902: 894: 875: 873: 872: 867: 865: 864: 860: 847: 846: 842: 829: 821: 731: 729: 728: 723: 718: 717: 713: 658: 656: 655: 650: 636: 634: 626: 618: 596: 594: 593: 588: 583: 538: 536: 535: 530: 498: 496: 488: 471: 439:Systems modeling 351:dam management. 32:hydrologic model 21: 3422: 3421: 3417: 3416: 3415: 3413: 3412: 3411: 3392: 3391: 3390: 3385: 3344: 3298: 3284:Energy modeling 3272: 3216: 3192:Ecosystem model 3168: 3163: 3133: 3128: 3112: 3075: 3049: 3011: 2978: 2930: 2906:Drip irrigation 2887: 2884: 2847: 2842: 2797: 2793: 2740: 2736: 2685: 2681: 2636: 2632: 2585: 2581: 2574: 2570: 2563: 2556: 2503: 2499: 2492: 2478: 2474: 2469: 2465: 2460: 2456: 2451: 2447: 2408: 2404: 2395: 2393: 2385: 2384: 2380: 2375: 2371: 2358:(11): 559–572. 2344: 2340: 2301: 2297: 2270: 2266: 2235: 2231: 2192: 2188: 2157: 2153: 2122: 2118: 2087: 2083: 2038: 2034: 1995:Gelhar, Lynn W. 1992: 1988: 1983: 1979: 1972: 1968: 1933: 1929: 1890: 1886: 1839: 1835: 1790: 1786: 1779: 1760:10.1.1.295.9820 1747: 1743: 1738: 1734: 1722: 1718: 1687: 1683: 1644: 1640: 1631: 1627: 1618: 1617: 1613: 1597: 1596: 1590: 1588: 1581:"Archived copy" 1579: 1578: 1574: 1566: 1562: 1547:10.1002/hyp.162 1523: 1519: 1510: 1506: 1475: 1471: 1426: 1422: 1418: 1396: 1364: 1320: 1318:Numeric methods 1304: 1299: 1263: 1249: 1247: 1241: 1237: 1224: 1219: 1202: 1199: 1198: 1168: 1160: 1158: 1139: 1131: 1129: 1127: 1124: 1123: 1089: 1081: 1079: 1066: 1058: 1056: 1041: 1037: 1033: 1023: 1019: 1018: 1016: 1011: 1008: 1007: 977: 969: 967: 952: 948: 943: 940: 939: 893: 892: 890: 887: 886: 856: 852: 848: 838: 834: 830: 820: 812: 809: 808: 792: 761:reaction factor 709: 702: 698: 678: 675: 674: 627: 619: 617: 612: 609: 608: 579: 550: 547: 546: 489: 472: 470: 468: 465: 464: 373: 357: 320:Factor analysis 284:autocorrelation 276: 220: 201: 125: 123:Process analogs 101:Reynolds number 76: 68:process analogs 49: 28: 23: 22: 15: 12: 11: 5: 3420: 3410: 3409: 3404: 3387: 3386: 3384: 3383: 3378: 3373: 3371:Systems theory 3368: 3363: 3358: 3352: 3350: 3349:Related topics 3346: 3345: 3343: 3342: 3337: 3335:Economic model 3332: 3327: 3322: 3317: 3312: 3306: 3304: 3300: 3299: 3297: 3296: 3291: 3286: 3280: 3278: 3277:Sustainability 3274: 3273: 3271: 3270: 3265: 3260: 3255: 3250: 3245: 3240: 3235: 3230: 3224: 3222: 3218: 3217: 3215: 3214: 3209: 3204: 3199: 3194: 3189: 3184: 3182:Cellular model 3178: 3176: 3170: 3169: 3162: 3161: 3154: 3147: 3139: 3130: 3129: 3127: 3126: 3120: 3118: 3117:Related topics 3114: 3113: 3111: 3110: 3104: 3099: 3094: 3089: 3083: 3081: 3077: 3076: 3074: 3073: 3068: 3063: 3057: 3055: 3051: 3050: 3048: 3047: 3042: 3037: 3032: 3027: 3021: 3019: 3013: 3012: 3010: 3009: 3004: 2999: 2994: 2988: 2986: 2980: 2979: 2977: 2976: 2971: 2966: 2961: 2956: 2951: 2946: 2940: 2938: 2932: 2931: 2929: 2928: 2923: 2918: 2913: 2908: 2903: 2897: 2895: 2889: 2888: 2883: 2882: 2875: 2868: 2860: 2854: 2853: 2846: 2845:External links 2843: 2841: 2840: 2791: 2734: 2699:(2): 497–508. 2679: 2630: 2579: 2568: 2554: 2497: 2490: 2472: 2463: 2454: 2445: 2418:(3): 443–449. 2402: 2378: 2369: 2338: 2311:(1): 213–223. 2295: 2264: 2229: 2186: 2167:(1–2): 19–39. 2151: 2132:(1–4): 71–89. 2116: 2081: 2052:(4): 751–763. 2032: 1986: 1977: 1966: 1927: 1900:(4): 597–611. 1884: 1833: 1804:(1): 147–155. 1784: 1777: 1741: 1732: 1716: 1681: 1654:(4): 447–461. 1638: 1632:Beard, Leo R. 1625: 1611: 1572: 1560: 1533:(3): 479–492. 1517: 1504: 1469: 1419: 1417: 1414: 1413: 1412: 1407: 1402: 1395: 1392: 1363: 1360: 1329:finite-element 1319: 1316: 1303: 1300: 1298: 1295: 1294: 1293: 1282: 1279: 1272: 1269: 1266: 1261: 1258: 1255: 1252: 1244: 1240: 1233: 1230: 1227: 1223: 1218: 1215: 1212: 1209: 1206: 1189: 1188: 1174: 1171: 1166: 1163: 1157: 1154: 1151: 1145: 1142: 1137: 1134: 1110: 1109: 1095: 1092: 1087: 1084: 1078: 1072: 1069: 1064: 1061: 1055: 1052: 1044: 1040: 1036: 1031: 1026: 1022: 1015: 998: 997: 983: 980: 975: 972: 966: 963: 960: 955: 951: 947: 930: 929: 918: 915: 912: 909: 906: 900: 897: 877: 876: 863: 859: 855: 851: 845: 841: 837: 833: 827: 824: 819: 816: 791: 788: 787: 786: 733: 732: 721: 716: 712: 708: 705: 701: 697: 694: 691: 688: 685: 682: 660: 659: 648: 645: 642: 639: 633: 630: 625: 622: 616: 598: 597: 586: 582: 578: 575: 572: 569: 566: 563: 560: 557: 554: 540: 539: 528: 525: 522: 519: 516: 513: 510: 507: 504: 501: 495: 492: 487: 484: 481: 478: 475: 372: 369: 356: 353: 275: 272: 219: 216: 206:are a type of 200: 197: 124: 121: 82:Detail of the 75: 72: 48: 45: 26: 9: 6: 4: 3: 2: 3419: 3408: 3405: 3403: 3400: 3399: 3397: 3382: 3379: 3377: 3374: 3372: 3369: 3367: 3364: 3362: 3359: 3357: 3354: 3353: 3351: 3347: 3341: 3338: 3336: 3333: 3331: 3330:Crime mapping 3328: 3326: 3323: 3321: 3318: 3316: 3313: 3311: 3308: 3307: 3305: 3301: 3295: 3292: 3290: 3287: 3285: 3282: 3281: 3279: 3275: 3269: 3266: 3264: 3261: 3259: 3256: 3254: 3251: 3249: 3246: 3244: 3241: 3239: 3238:Climate model 3236: 3234: 3231: 3229: 3226: 3225: 3223: 3221:Environmental 3219: 3213: 3210: 3208: 3205: 3203: 3200: 3198: 3195: 3193: 3190: 3188: 3185: 3183: 3180: 3179: 3177: 3175: 3171: 3167: 3160: 3155: 3153: 3148: 3146: 3141: 3140: 3137: 3125: 3122: 3121: 3119: 3115: 3108: 3105: 3103: 3100: 3098: 3095: 3093: 3090: 3088: 3085: 3084: 3082: 3078: 3072: 3069: 3067: 3064: 3062: 3059: 3058: 3056: 3054:Problem soils 3052: 3046: 3043: 3041: 3038: 3036: 3033: 3031: 3028: 3026: 3023: 3022: 3020: 3018: 3014: 3008: 3005: 3003: 3000: 2998: 2995: 2993: 2990: 2989: 2987: 2985: 2981: 2975: 2972: 2970: 2967: 2965: 2962: 2960: 2957: 2955: 2952: 2950: 2949:Tile drainage 2947: 2945: 2942: 2941: 2939: 2937: 2933: 2927: 2924: 2922: 2919: 2917: 2914: 2912: 2909: 2907: 2904: 2902: 2899: 2898: 2896: 2894: 2890: 2881: 2876: 2874: 2869: 2867: 2862: 2861: 2858: 2852: 2849: 2848: 2836: 2832: 2827: 2822: 2818: 2814: 2810: 2806: 2802: 2795: 2787: 2783: 2779: 2775: 2770: 2765: 2761: 2757: 2753: 2749: 2745: 2738: 2730: 2726: 2722: 2718: 2714: 2710: 2706: 2702: 2698: 2694: 2690: 2683: 2675: 2671: 2666: 2661: 2657: 2653: 2649: 2645: 2641: 2634: 2626: 2622: 2617: 2612: 2607: 2602: 2598: 2594: 2590: 2583: 2577: 2572: 2566: 2561: 2559: 2550: 2546: 2541: 2536: 2532: 2528: 2524: 2520: 2516: 2512: 2508: 2501: 2493: 2487: 2483: 2476: 2467: 2458: 2449: 2441: 2437: 2433: 2429: 2425: 2421: 2417: 2413: 2406: 2392: 2388: 2382: 2373: 2365: 2361: 2357: 2353: 2349: 2342: 2334: 2330: 2326: 2322: 2318: 2314: 2310: 2306: 2299: 2291: 2287: 2283: 2279: 2275: 2268: 2260: 2256: 2252: 2248: 2244: 2240: 2233: 2225: 2221: 2217: 2213: 2209: 2205: 2201: 2197: 2190: 2182: 2178: 2174: 2170: 2166: 2162: 2155: 2147: 2143: 2139: 2135: 2131: 2127: 2120: 2112: 2108: 2104: 2100: 2096: 2092: 2085: 2077: 2073: 2068: 2063: 2059: 2055: 2051: 2047: 2043: 2036: 2028: 2024: 2020: 2016: 2012: 2008: 2004: 2000: 1996: 1990: 1981: 1975: 1970: 1962: 1958: 1954: 1950: 1946: 1942: 1938: 1931: 1923: 1919: 1915: 1911: 1907: 1903: 1899: 1895: 1888: 1880: 1876: 1872: 1868: 1864: 1860: 1856: 1852: 1848: 1844: 1837: 1829: 1825: 1820: 1815: 1811: 1807: 1803: 1799: 1795: 1788: 1780: 1778:9783319433158 1774: 1770: 1766: 1761: 1756: 1752: 1745: 1736: 1729: 1725: 1720: 1712: 1708: 1704: 1700: 1696: 1692: 1685: 1677: 1673: 1669: 1665: 1661: 1657: 1653: 1649: 1642: 1635: 1629: 1621: 1615: 1607: 1601: 1587:on 2015-12-29 1586: 1582: 1576: 1570: 1564: 1556: 1552: 1548: 1544: 1540: 1536: 1532: 1528: 1521: 1514: 1508: 1500: 1496: 1492: 1488: 1484: 1480: 1473: 1465: 1461: 1456: 1451: 1447: 1443: 1439: 1435: 1431: 1424: 1420: 1411: 1408: 1406: 1403: 1401: 1398: 1397: 1391: 1389: 1385: 1380: 1377: 1368: 1359: 1357: 1353: 1349: 1345: 1341: 1336: 1332: 1330: 1326: 1315: 1313: 1309: 1280: 1277: 1270: 1267: 1264: 1256: 1250: 1242: 1238: 1231: 1228: 1225: 1221: 1216: 1210: 1204: 1197: 1196: 1195: 1193: 1172: 1164: 1155: 1152: 1149: 1143: 1135: 1122: 1121: 1120: 1118: 1114: 1093: 1085: 1076: 1070: 1062: 1053: 1050: 1042: 1038: 1029: 1024: 1013: 1006: 1005: 1004: 1002: 981: 973: 964: 961: 958: 953: 945: 938: 937: 936: 934: 916: 910: 907: 904: 895: 885: 884: 883: 881: 861: 857: 853: 849: 843: 839: 835: 831: 825: 822: 817: 814: 807: 806: 805: 803: 799: 796: 784: 780: 776: 773: 772: 771: 768: 766: 762: 758: 753: 752:can be used. 751: 746: 745: 737: 714: 710: 706: 703: 699: 695: 692: 686: 683: 680: 673: 672: 667: 663: 646: 643: 640: 637: 631: 628: 623: 620: 614: 607: 606: 605: 603: 584: 580: 573: 567: 564: 558: 552: 545: 544: 543: 523: 517: 514: 508: 502: 499: 493: 490: 482: 476: 473: 463: 462: 461: 458: 456: 452: 447: 446: 442: 440: 435: 432: 427: 424: 420: 415: 413: 409: 405: 401: 397: 393: 389: 385: 377: 368: 364: 361: 352: 349: 348:Markov chains 345: 342: 338: 335: 331: 329: 325: 321: 317: 315: 311: 307: 303: 299: 297: 293: 289: 285: 281: 271: 269: 265: 261: 257: 251: 249: 245: 241: 237: 233: 229: 225: 215: 213: 209: 205: 196: 192: 190: 186: 182: 178: 174: 170: 169:concentration 167:, and solute 166: 162: 158: 154: 150: 146: 142: 138: 137:Fourier's law 134: 130: 120: 112: 108: 106: 105:Froude number 102: 96: 89: 85: 80: 74:Scale analogs 71: 69: 65: 64:scale analogs 60: 58: 54: 53:analog models 47:Analog models 40: 36: 33: 19: 3252: 3071:Saline soils 3066:Alkali soils 2996: 2808: 2804: 2794: 2751: 2747: 2737: 2696: 2692: 2682: 2647: 2643: 2633: 2616:10261/253007 2599:(13): 2238. 2596: 2592: 2582: 2571: 2514: 2510: 2500: 2481: 2475: 2466: 2457: 2448: 2415: 2411: 2405: 2394:. 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2282:0083-1131 2224:1944-7973 2076:1944-7973 2027:1944-7973 1922:1099-1085 1879:122128745 1871:0931-1955 1755:CiteSeerX 1676:1944-7973 1555:129919508 1464:1607-7938 1268:− 1243:γ 1239:∮ 1229:π 1170:∂ 1165:τ 1162:∂ 1156:μ 1153:− 1141:∂ 1133:∂ 1091:∂ 1083:∂ 1068:∂ 1060:∂ 1051:− 1035:∂ 1021:∂ 979:∂ 971:∂ 950:∇ 914:∇ 908:− 899:→ 777:= 0.0123 744:Example 2 704:− 696:− 644:− 515:− 445:Example 1 412:numerical 310:Bivariate 286:, or the 133:Ohm's law 3124:Sand dam 1828:14783093 1600:cite web 1394:See also 1352:MIKE SHE 781:+ 0.138 396:ordinary 240:kurtosis 236:skewness 2813:Bibcode 2756:Bibcode 2701:Bibcode 2652:Bibcode 2519:Bibcode 2420:Bibcode 2313:Bibcode 2290:1422999 2247:Bibcode 2204:Bibcode 2169:Bibcode 2134:Bibcode 2099:Bibcode 2054:Bibcode 2007:Bibcode 1949:Bibcode 1902:Bibcode 1851:Bibcode 1806:Bibcode 1699:Bibcode 1656:Bibcode 1535:Bibcode 1487:Bibcode 1442:Bibcode 1344:MODFLOW 1312:Fourier 1308:Laplace 785:- 0.112 264:Pearson 226:(e.g., 224:moments 218:Moments 161:voltage 157:solutes 90:, 2006) 3303:Social 2833:  2784:  2776:  2727:  2719:  2672:  2623:  2547:  2488:  2438:  2331:  2288:  2280:  2222:  2074:  2025:  1920:  1877:  1869:  1826:  1775:  1757:  1674:  1553:  1462:  1382:Model 1354:, and 1348:FEFLOW 600:where 423:system 314:linear 288:T-test 266:, and 260:Gumbel 155:, and 139:, and 2944:Ditch 2782:S2CID 2725:S2CID 2593:Water 2545:S2CID 1875:S2CID 1824:S2CID 1551:S2CID 402:, or 294:, or 2831:ISSN 2774:ISSN 2717:ISSN 2670:ISSN 2621:ISSN 2486:ISBN 2436:ISSN 2329:ISSN 2286:OCLC 2278:ISSN 2220:ISSN 2072:ISSN 2023:ISSN 1918:ISSN 1867:ISSN 1773:ISBN 1672:ISSN 1606:link 1460:ISSN 1356:WEAP 1340:SWAT 1327:and 1310:and 449:The 326:are 322:and 228:mean 179:are 171:(or 153:heat 145:flux 2821:doi 2764:doi 2709:doi 2660:doi 2611:hdl 2601:doi 2535:hdl 2527:doi 2515:569 2428:doi 2360:doi 2321:doi 2255:doi 2243:205 2212:doi 2177:doi 2142:doi 2130:173 2107:doi 2095:254 2062:doi 2015:doi 1957:doi 1910:doi 1859:doi 1814:doi 1765:doi 1707:doi 1695:349 1664:doi 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Index

Hydrological modelling

analog models
mathematical models
scale analogs
process analogs

Mississippi River Basin Model
US Army Corps of Engineers
Reynolds number
Froude number

Darcy's law
Ohm's law
Fourier's law
Fick's law
flux
electricity
heat
solutes
voltage
temperature
concentration
chemical potential
hydraulic conductivity
electrical conductivity
thermal conductivity
diffusion coefficient
Statistical models
mathematical model

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