Tuomo Karvonen

Lateral subsurface stormflow and solute transport in a forested hillslope: A combined measurement and modeling approach

Preferential flow dominates water movement and solute transport in boreal forest hillslopes. However, only a few model applications to date have accounted for preferential flow at forest sites. Here we present a parallel and coupled simulation of flow and transport processes in the preferential flow domain and soil matrix of a forested hillslope section in Kangaslampi, Finland, using a new, three-dimensional, physically based dual-permeability model. Our aim is to simulate lateral subsurface stormflow and solute transport at the slope during a chloride tracer experiment, and to investigate the role of preferential flow in the tracer transport. The model was able to mimic the observed tracer transport during tracer irrigation, but overestimated the dilution velocity of the tracer plume in the highly conductive soil horizons near the soil surface after changing the irrigation to tracer-free water. According to the model, 140 times more chloride was transported downslope in the preferential flow domain than in the soil matrix during the tracer irrigation. The simulations showed, together with reference simulations with a traditional one pore domain model, that a two pore domain approach was required to simulate the observed flow and transport event. The event was characterized by the transmissivity feedback phenomenon and controlled by preferential flow mechanisms, in particular by lateral by-pass flow. According to our results, accounting for the slow-flow and fast-flow domains of soil, as well as the water and solute exchange between the domains, is essential for a successful simulation of flow and solute transport in preferential flow dominated hillslopes.

Modelling crop growth and biomass partitioning to shoots and roots in relation to nitrogen and water availability, using a maximization principle

Many crop models relate the allocation of dry matter between shoots and roots exclusively to the crop development stage. Such models may not take into account the effects of changes in environment on allocation, unless the allocation parameters are altered. In this paper a crop model with a dynamic allocation parameter for dry matter between shoots and roots is described. The basis of the model is that a plant allocates dry matter such that its growth is maximized. Consequently, the demand and supply of carbon, nitrogen, and water is maintained in balance. This model supports the hypothesis that a functional equilibrium exists between shoots and roots.This paper explains the mathematical computation procedure of the crop model. Moreover, an analysis was made of the ability of a crop model to simulate plant dry matter production and allocation of dry matter between plant organs. The model was tested using data from a greenhouse experiment in which spring wheat (Triticum aestivum L.) was grown under different soil moisture and nitrogen (N) levels.Generally, the model simulations agreed well with data recorded for total plant dry matter. For validation data the coefficient of determination (r2) between simulated and measured shoot dry weight was 0.96. For the validation treatments r2 was slightly lower, 0.94. In addition to dry matter production the model succeeded satisfactorily in simulating the dry weight of different plant organs. The response of simulated root to shoot ratio to the level of soil moisture was mainly in accordance with the measured data. In contrast, the simulated ratio seemed to be insensitive to the changes in the levels soil N concentration used in the experiment.The data used in the present study were not extensive, and more data are needed to validate the model. However, the results showed that the model responses to the changes in soil N and water level were realistic and mostly agreed with the data. Thus, we suggest that the model and the method employed to allocate dry matter between roots and shoots are useful when modelling the growth of crops under N and water limited conditions.

A semi-distributed approach to rainfall-runoff modelling—a case study in a snow affected catchment

Abstract A semi-distributed hydrological model was applied to a small forested catcment in southern Finland. The aim was to demonstrate how differences in terrain properties could be taken into account in modelling runoff generation, and to test how well the presented model simulated streamflow with only limited calibration. Modelling was based on subdivision of a catchment into topographically similar areas, which were identified from a digital elevation model. The water balance in each area was calculated using a hillslope-scale model. Discharges from the set of hillsope-scale models were combined with the aid of a routing procedure to yield the total streamflow at the catchment outlet. The catchment receives approximately 30% of the annual precipitation as snow, and thus a snow model was required in winter periods. The presented semi-distributed model was capable of reproducing fairly well the measured streamflow when only two model parameters were calibrated against streamflow. The results suggested that unlike the cumulative runoff, the temporal variability of runoff response was affected by terrain topography. Only minor differences were detected in reproduction of streamflow between the semi-distributed model and a simple lumped model IHACRES used as a reference.

Application of a two-dimensional model to calculate water balance of an agricultural hillslope

Abstract The objective was to simulate runoff production on an agricultural hillslope in Southern Finland. Water balance was calculated using a quasi-two-dimensional model describing vertical soil moisture distribution and horizontal water movement along a hillslope strip. The model accounted for the production of saturated overland flow on the exfiltration part of the hillslope. The model results were assessed against measurements of surface runoff, subsurface drainage flow, and water table level, which were available at individual field sections for years 1995-96. Intensive runoff events during summer and autumn rainfalls were the primary focus in the modeling application. The model performed well during wet periods when water table remained close to the soil surface, but the results were less satisfactory during dry periods.

Modelling crop growth and biomass partitioning to shoots and roots in relation to nitrogen and water availability, using a maximization principle. II. Simulation of crop nitrogen balance

Abstract This study analysed of the ability of a crop model to simulate crop nitrogen (N) balance. The model was originally developed to serve as a foundation to develop a decision-making tool to analyse the impact of water management and nitrogen fertilization on crop yield. The model included a dynamic parameter for allocation of dry matter between root and shoot allowing root to shoot ratio to vary according to differing environmental conditions. The new allocation parameter was introduced in order to make the model more applicable under water and nitrogen limited growing conditions. Two wheat ( Triticum aestivum L.) data sets were used to test the model simulations. Generally, the model simulations agreed well with the recorded data on crop N uptake. The relationship between the actual and simulated amount of N taken up by the crop was close in the calibration treatments of a greenhouse experiment. The coefficient of determination ( r 2 ) of the regression line (simulated value=independent variable, measured value=dependent variable) was 0.90. The r 2 was 0.83 for the validation data. In the field experiments, the r 2 values were 0.91 for the calibration data and 0.82 for the validation data. In field data, the model underestimated in some cases the crop N uptake during the period when actual shoot dry weight increased exponentially in spring. Therefore, methods used in computation of nitrogen uptake have to be analysed further. Plant organ N content was simulated satisfactorily for both greenhouse and field data. However, the range over which the simulated values varied was larger than in the actual data. The results from the study indicate that our model is capable of simulating the crop N balance and we suggest that the model could be used when developing an N application decision tool for field crops. However, the availability of N and soil water were provided as inputs in the present study. Thus, the model should be integrated with models simulating below ground processes in the future. Moreover, the model should be further validated with actual field data.