Navin K. C. Twarakavi

Selected HYDRUS modules for modeling subsurface flow and contaminant transport as influenced by biological processes at various scales

A large number of modifications or special modules of the HYDRUS software packages have been developed during the past several years to evaluate the effects of a range of biohydrological processes on subsurface water flow and the transport of various chemicals and contaminants. The objective of this manuscript is to briefly review the different modules that were included, and to present various applications illustrating the effects of biological processes on water flow and solute transport and reactions in variably-saturated media.

INVERSE MODELING OF VADOSE ZONE FLOW PROCESSES USING SQUARED ε-INSENSITIVITY LOSS FUNCTION

Inverse modeling of vadose zone flow processes using squared ε-insensitivity loss function An accurate representation of reality in numerical variably-saturated flow models requires reliable estimates of necessary model parameters. Inverse modeling seeks to estimate parameters such as the saturated and residual water contents, the saturated hydraulic conductivity, the shape parameters of the soil hydraulic functions, using easily attainable observations of actual or cumulative water fluxes, pressure heads, water contents, and concentrations. The inverse procedure usually combines the nonlinear least-squares-based (SSQ) parameter optimization method with a numerical solution of the variably-saturated flow and transport equations. The SSQ-based inverse method is however sensitive to outliers. A novel Squared ε-Insensitive Loss Function (SILF) approach is introduced in this study. The SILF approach is inspired by the ε-insensitive loss function proposed by Vapnik (1995). The objective function used in the SILF approach is similar to the least-squares objective function, except that it penalizes only for errors greater than a certain predefined acceptable error term ε. The SILF approach shows an improved performance over the SSQ approach in estimating the soil hydraulic parameters. Apart from providing robust estimates of the soil hydraulic parameters, the SILF approach also gives an approximation of the relative measurement error during sampling. Inverzné modelovanie prúdenia vody vo vodou nenasýtenej pôde s použitím necitlivostnej stratovej funkcie ε Presná reprezentácia skutočností v numerických modeloch prúdenia vo vodou nenasýtenej pôde vyžaduje spoľahlivé určenie potrebných parametrov modelu. Inverzným modelovaním sa snažíme o určenie takých parametrov, ako sú reziduálna vlhkosť pôdy, nasýtená hydraulická vodivosť, tvarové parametre hydraulických funkcií pôdy, využijúc ľahko realizovateľné pozorovania momentálnych alebo kumulatívnych tokov vody, tlakových výšok, vlhkostí pôdy a koncentrácií rozpustených látok. Inverzná procedúra obyčajne kombinuje nelineárnu optimalizáciu parametrov založenú na metóde najmenších štvorcov (SSQ) s numerickým riešením transportných rovníc vo vodou nenasýtenej pôde. Táto metóda (SSQ) je však citlivá na náhodné chyby. Nová, necitlivostná stratová funkcia s necitlivosťou ε(SILF), použitá v tejto štúdii, bola inšpirovaná návrhom publikovaným Vapnikom (1995). Optimalizovaná funkcia použitá v prístupe SILF je podobná tej, ktorá sa používa v metóde najmenších štvorcov s tou výnimkou, že táto penalizuje len chyby väčšie ako je určitá preddefinovaná akceptovateľná chyba ε. Pri určovaní hydraulických parametrov pôdy táto metóda SILF preukázala svoje prednosti pred prístupom SSQ. Okrem toho, že metóda SILF dáva robustné odhady hydraulických parametrov pôdy, umožňuje tiež aproximáciu relatívnych chýb merania počas odberu vzoriek.

Influence of Spatial Scales on the Performance of Saturated Subsurface Flow and Transport Models

Numerical modeling of saturated subsurface flow and transport has been widely used in the past using different numerical schemes such as finite difference and finite element methods. Such modeling often involves discretization of the problem in spatial and temporal scales. The choice of the spatial and temporal scales for a modeling scenario is often not straightforward. For example, a basin-scale saturated flow and transport analysis demands larger spatial and temporal scales than a meso-scale study, which in turn has larger scales compared to a pore-scale study. The choice of spatial-scale is often dictated by the computational capabilities of the modeler as well as the availability of fine-scale data. In this study, we analyze the impact of different spatial scales and scaling procedures on saturated subsurface flow and transport simulations.