MIKE SHE Model Research Articles

Parameterisation and scaling of the land surface model for use in a coupled climate-hydrological model

Summary Climate impact studies in hydrology have traditionally neglected the land–atmosphere feedback. Hydrological models are forced with output from climate models but neglecting this feedback may lead to an inaccurate estimation of evapotranspiration (ET). Two-way coupling of a hydrological model and a climate model can overcome this problem by linking the two models through a shared land–atmosphere process description. In this study we analyse the hydrological model MIKE SHE using a two-layer energy-based ET model for use in a coupling with a regional climate model (RCM). The value of coupling to MIKE SHE is that it makes it possible to include lateral transport of surface water and groundwater not generally treated in RCM’s and to represent human interventions like groundwater pumping, irrigation schemes, etc. for adaptation studies. The hydrological model is applied to the FIFE site to investigate the effects of model resolution and parameter scales. The area of interest corresponds to a RCM grid cell. The hydrological model is parameterized with effective parameters assessed directly from field data at the site and literature. Using only these observed data and literature estimates to parameterise the model, it is able to reproduce the observed ET, sensible heat flux and to some extent surface soil moisture content; over a whole growing season. Hydrological simulations carried out over a range of spatial grids from 240 m to 15 km show that, for this case, the areal average ET appears to be insensitive to model resolution. The model is able to reproduce some of the spatial variability within the area, but not the exact pattern. By running the hydrological model at the highest resolution with uniform atmospheric input we examined the effect of using coarser resolution climate forcing, for example from a RCM. The areal mean ET and soil moisture (SM) temporal variations are reproduced quite well, but the spatial variability in the hydrological response is substantially underestimated; mainly because of the uniform precipitation. Our results are therefore encouraging for using this type of energy-based model in a coupling between a regional climate model and a distributed hydrological model. As the FIFE area is a relatively homogeneous site, additional tests are needed at heterogeneous sites to validate whether our findings are in general valid.

MIKE SHE: Model Use, Calibration, and Validation

MIKE SHE is a physically based, integrated water resources model that simulates both surface and subsurface water dynamics. These dynamics include interception, evapotranspiration, overland flow, channel flow, unsaturated flow, and saturated zone flow. The model can also simulate limited surface water quality processes using the advection dispersion equation and groundwater quality with a random-walk tracking method. This article is intended to describe the components of MIKE SHE and its calibration, validation, and applications. Given the deterministic, physically based characteristics of MIKE SHE and the large number of processes it simulates simultaneously, the number of parameters to calibrate can be large. A combination of user experience with the model, knowledge of the problem being solved, and an automatic calibration feature help in selecting the most sensitive parameters to calibrate. A case study describing the use of the MIKE SHE model, coupled with the hydraulic MIKE 11 model, to solve water flow in agricultural reservoirs in south Florida is presented. The problem required the use of the MIKE SHE model due to the high groundwater and overland flow interactions as well as the complex flow patterns inside the reservoir. The horizontal and vertical saturated hydraulic conductivities and the leakage coefficient were identified as the calibration parameters. The model was calibrated and evaluated for two reservoirs using two different time periods. Results showed matching between measured and simulated data for both reservoirs for the calibration and validation periods. The coupled MIKE SHE/MIKE 11 model has the capabilities to simulate complex hydrological processes and their interactions, which few other watershed models can match, and is suitable for current problems, such as the effects of climate change and land use change.

Impact assessment of projected climate change on the hydrological regime in the SE Alps, Upper Soča River basin, Slovenia

According to climate change projections, the Alps will be one of the most affected regions in Europe. A basis for adaptation measures to climate changes is the quantification of the impact. This study investigates the impact of projected climate change on the hydrological cycle in the Upper Soca River basin. It is based on the use of climate model data as input for hydrological modelling. The climatic input data used were generated by a global climate model (IPCC A1B emission scenario) and downscaled for local use. Hydrological modelling was performed using the distributed hydrological model MIKE SHE. The simulated impact was quantified by comparing results of the hydrological modelling for the control period (1971–2000) and different scenario periods (2011–2040, 2041–2070, 2071–2100). The climate projections show an increase in the average temperature (+0.9, +2.3, +3.8°C) and negligible changes in average precipitation amounts in the scenario periods. More distinctive are changes in the temporal pattern of mean monthly values (up to +5.2°C and ±45% for precipitation), which result in warmer and wetter winters and hotter and drier summers in the scenario periods. The projected rise in temperature is reflected in the increased actual evapotranspiration, the reduction of snow amount and summer groundwater recharge. Changes of monthly and period average discharges follow the trends of the meteorological variables. Changes in precipitation patterns have a major influence on the projected hydrological cycle and are the most important source of uncertainty. Estimated extreme flows indicated increased hazards related to floods, especially in the near-future scenario period, while in the far future scenario period, distinctive drought conditions are projected.

Evaluation of the MIKE SHE Model in a Cold Region

Given its rapid urbanization, the Canagagigue Creek watershed, located in Grand River Basin (Ontario, Canada), is subjected to shifting hydrological patterns. Consequently, surface runoff was simulated using a watershed-scale model MIKE SHE. The model was calibrated with four years of data and validated with another four years data. Satisfactory levels of overall correlation (R2) between monitored and model-simulated monthly runoff were: 0.87 and 0.77 for the calibration and validation periods, respectively. Corresponding values of the Nash-Sutcliffe coefficient, 0.86 and 0.75, were similar. The model was also used to simulate different management scenarios, urbanization, deforestation, conversion of pastureland into agriculture, diversification of corn system into cash crops, and application of tile drainage. Urbanization showed little impact on surface runoff as increase in urbanized area was a small fraction of the watershed area. Deforestation considerably increased (11%) the total flow. Change in cropping patterns and installation of drainage system had marginal impacts on the surface runoffs. Overall, the model was able to simulate surface runoff reasonably well on monthly and annual basis, although slightly poorer on daily basis. It was concluded that the model could be used to investigate hydrological behaviour of the watersheds in cold climate.

Impact of Precipitation Spatial Resolution on the Hydrological Response of an Integrated Distributed Water Resources Model

Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff, recharge and groundwater head was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both affected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low for a catchment size above 250 km2, and the effect is negligible when the entire catchment area of approximately 1000 km2 is considered. In the present case the highest resolution of 500 m was found to result in the best representation of the hydrological response at subcatchment scale. Stream discharge, groundwater recharge, and groundwater head were also affected by the method for correction of systematic errors in precipitation measurements. The results underscored the importance of using a spatial resolution of the precipitation input that captures the overall precipitation characteristics for the considered catchment or subcatchment. As long as the average precipitation of the considered catchment or subcatchment is accurately estimated, the spatial resolution seems less important when the integrated response in the form of stream flow is considered.

Analysis of the impact of climate change on groundwater related hydrological fluxes: a multi-model approach including different downscaling methods

Abstract. Climate change related modifications in the spatio-temporal distribution of precipitation and evapotranspiration will have an impact on groundwater resources. This study presents a modelling approach exploiting the advantages of integrated hydrological modelling and a broad climate model basis. We applied the integrated MIKE SHE model on a perialpine, small catchment in northern Switzerland near Zurich. To examine the impact of climate change we forced the hydrological model with data from eight GCM-RCM combinations showing systematic biases which are corrected by three different statistical downscaling methods, not only for precipitation but also for the variables that govern potential evapotranspiration. The downscaling methods are evaluated in a split sample test and the sensitivity of the downscaling procedure on the hydrological fluxes is analyzed. The RCMs resulted in very different projections of potential evapotranspiration and, especially, precipitation. All three downscaling methods reduced the differences between the predictions of the RCMs and all corrected predictions showed no future groundwater stress which can be related to an expected increase in precipitation during winter. It turned out that especially the timing of the precipitation and thus recharge is very important for the future development of the groundwater levels. However, the simulation experiments revealed the weaknesses of the downscaling methods which directly influence the predicted hydrological fluxes, and thus also the predicted groundwater levels. The downscaling process is identified as an important source of uncertainty in hydrological impact studies, which has to be accounted for. Therefore it is strongly recommended to test different downscaling methods by using verification data before applying them to climate model data.

Analysis of the development of a hydrological balance for future decades in the Senianska depression in the Eastern Slovak lowland

Analysis of the development of a hydrological balance for future decades in the Senianska depression in the Eastern Slovak lowlandThe goal of the article was to analyze the hydrological balance for future decades in a pilot area in the Eastern Slovak lowland. The aim was to set up the physically-based Mike SHE hydrological model for the modeling hydrological balance in the selected wetland ecosystem in the Eastern Slovak Lowland. The pilot area - the Senianska depression is located near the village of Senne, between the Laborec and Uh Rivers. Specifically, it is a traditional landscape of meadows, marshes, cultivated soil, small water control structures and forests. To get a complete model set up for simulating elements of the hydrologic balance in the pilot area, it was necessary to devise a model for a larger area, which includes the pilot area - the Senianska depression. Therefore, both the Mike SHE model was set up for the Laborec River basin (a model domain of 500 × 500 m) and the Čierna voda River basin (a model domain of 100 × 100 m), for the simulation period of 1981-2007, is order to get the boundary conditions (overland flow depth, water levels, discharges and groundwater table) for the model of the pilot area. The Mike SHE model constructed for the pilot area - the Senianska depression (a model domain of 1 × 1 m) -was used to simulate the elements of the hydrological balance for the existing conditions during the simulation period of 1983-2007 and for climate scenarios for the simulation period of 1983-2100. The results of the simulated elements of the hydrological balance for the existing conditions were used for a comparison of the evolution of the hydrologic conditions in the past, for identifying wet and flooded areas and for identifying the spatial distribution of the actual evapotranspiration in the pilot area. The built-up model with setting values was used for modeling the hydrological balance in changed conditions - climate change.

Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain

Abstract. Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (R2) and Nash-Sutcliffe's model efficiency (E). The E and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R2 varied from 0.60–0.99 for daily and monthly streamflow, and from 0.52–0.91 for daily water table depth. E changed from 0.53–0.96 for calibration and 0.51–0.98 for validation of daily and monthly streamflow, while E varied from 0.50–0.90 for calibration and 0.66–0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds.

Evaluation of the MIKE SHE Model for Application in the Loess Plateau, China1

Abstract: Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow‐dominant watershed (12 km2) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall‐runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.

Assessing the impacts of land use changes on watershed hydrology using MIKE SHE

A fully distributed, physically-based hydrologic modeling system, MIKE SHE, was used in this study to investigate whole-watershed hydrologic response to land use changes within the Gyeongancheon watershed in Korea. A grid of 200 × 200 m was established to represent spatial variations in geology, soil, and land use. Initial model performance was evaluated by comparing observed and simulated streamflow from 1988 to 1991. Results indicated that the calibrated MIKE SHE model was able to predict streamflow well during the calibration and validation periods. Proportional changes in five classes of land use within the watershed were derived from multi-temporal Landsat TM imageries taken in 1980, 1990 and 2000. These imageries revealed that the watershed experienced conversion of approximately 10% non-urban area to urban area between 1980 and 2000. The calibrated MIKE SHE model was then programmed to repeatedly analyze an artificial dataset under the various land use proportions identified in the Landsat TM imageries. The analysis was made to quantitatively assess the impact of land use changes (predominantly urbanization) on watershed hydrology. There were increases in total runoff (5.5%) and overland flow (24.8%) as a response to the land use change.

A remote sensing driven distributed hydrological model of the Senegal River basin

Summary Distributed hydrological models require extensive data amounts for driving the models and for parameterization of the land surface and subsurface. This study investigates the potential of applying remote sensing (RS) based input data in a hydrological model for the 350,000 km 2 Senegal River basin in West Africa. By utilizing remote sensing data to estimate precipitation, potential evapotranspiration (PET) and leaf area index (LAI) the model was driven entirely by remote sensing based data and independent of traditional meteorological data. The remote sensing retrievals were based on data from the geostationary METEOSAT-7 and the polar orbiting advanced very high resolution radiometer (AVHRR) sensors using well documented techniques. The distributed hydrological model MIKE SHE was calibrated and validated against observed discharge for six individual subcatchments during the period 1998–2005. The model generally performed well for both root mean square error (RMSE), water balance error (WBE) and correlation coefficient ( R 2 ). For comparison a model based on standard meteorological driving variables was developed for a single subcatchment. The two models based on remote sensing and conventional data, respectively, exhibited similar model performances. Simulated actual evapotranspiration (AET) was compared to measurements at point scale and good agreement was obtained both on an event basis and seasonally. Although the spatial model simulations cannot be evaluated quantitatively a comparison between spatial outputs of AET from both model setups was carried out. This revealed substantial differences in the spatial patterns of AET for the examined subcatchment, in spite of similar values of predicted discharge and average AET. The potential for driving large scale hydrological models using remote sensing data was clearly demonstrated and further emphasized by the presence of long time records and near real time accessibility of the satellite data sources.

Evapotranspiration estimates from eddy covariance towers and hydrologic modeling in managed forests in Northern Wisconsin, USA

Direct measurement of ecosystem evapotranspiration by the eddy covariance method and simulation modeling were employed to quantify the growing season (May–October) evapotranspiration (ET) of eight forest ecosystems representing a management gradient in dominant forest types and age classes in the Upper Great Lakes Region from 2002 to 2003. We measured net exchange of water vapor fluxes in a 63-year-old mature hardwood (MHW) stand, a 60-year-old mature red pine (MRP) stand, a 3-year-old young hardwood (YHW) stand, a 17-year-old intermediate hardwood (IHW) stand, a young red pine (YRP age 8) stand, an intermediate red pine (IRP age 21) stand, and two pine barren ecosystems burned 12 years (PB1) and 2 years (PB2) ago. Field data suggested that there were no significant differences in growing season (June–September) ET/precipitation ratio among all ecosystems in 2002. However, PB2 had significantly lower ET/precipitation than those of other ecosystems in 2003. The ratios were much higher for all ecosystems, up to 0.90 for IHW, during the peak summer months (June–July). PB2 was the lowest (0.64) during that period. Stand leaf area index alone did not explain ecosystem ET at the landscape scale. Seasonal ET values measured by the eddy covariance method were significantly lower than those simulated with a process-based hydrologic model, MIKE SHE. Our integration approach combined with field measurements and simulation modeling proved to be useful in providing a full picture of the effects of forest cover type change on landscape scale water balance at multiple temporal scales. The ET procedure used in the MIKE SHE model needs improvement to fully account for the effects of vapor pressure deficit on tree transpiration. Seasonal distributions of ET coincided with precipitation in the growing season, when fluxes estimated by both field and models were the highest. The simulation model suggests that removal of conifer forests in the study region may reduce ET immediately by 113–30 mm/year or about 20%, but our field data suggests that ET can recover within 8–25 years from re-growth of hardwood forests.

Predicted Concentrations for Pesticides in Drainage Dominated Catchments

Regulators need a reliable, precise and easy to use tool for predicting the occurrence of pesticides in drain water and catchments in agricultural areas. Occurrence depends on a wide range of substance and site specific factors and this study presents a simple model built on the results from simulations of a detailed model system that does not neglect or omit any of these factors. A drainage dominated sub-catchment (0.03 km2) of the Lillebaek catchment (4.4 km2) on Funen, Denmark, represented by the catchment model MIKE SHE is considered. Detailed analyses have been made with respect to geological and hydrodynamic conditions as well as measurements of pesticide concentrations in ground and surface waters. Maximum concentrations in drain water, the time for reaching this concentration and the time interval for exceeding the limit value have been derived empirically from MIKE SHE simulations using degradation rates and sorption coefficients values for 37 pesticides included in the Danish PATE database. The relatively hydrophilic bentazon and hydrophobic pendimethalin are used as model pesticides for illustration. A simple tool applicable for a wide range of pesticides has thus been designed based on detailed analyses of a limited number of pesticides. The user requirements are degradation rates, sorption coefficients, application rates and regulatory limit values for the pesticides of interest.

Climatic control on river discharge simulations, Zackenberg River drainage basin, northeast Greenland

AbstractA spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra‐ and inter‐annual discharge from the snow and glacierized Zackenberg River drainage basin (512 km2; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind‐blown snow, blowing‐snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow‐evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997–2001 (calibration period), 2001–2005 (validation period), and 2071–2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R2 = 0·58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44·6 m3 s−1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first‐order effects of climate change. For the period 2071–2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere–ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1·5 orders of magnitude greater (around 650 mmWE year−1) than from today 1997–2005 (around 430 mmWE year−1), mainly based on changes in negative glacier net mass balance. Copyright © 2007 John Wiley & Sons, Ltd.

Integrated physical and ecological management of the East River

We present an independent assessment of the health and water sustainability of the East River (Dongjiang) in South China, which is the source of nearly 80% of Hong Kong's water supply. Field measurements show that the water quality in the upper and middle reaches is generally good and well exceeds the drinking quality standard, with high bio-diversity. The streamflow of the East River Basin is satisfactorily simulated using both the distributed MIKE-SHE model and the lumped HSPF model. With an average streamflow of 760 m3/s, the River is able to satisfy the current water demand. Using the HSPF model, the water quality is found to have deteriorated in recent years. In addition to water supply, the River also supports a variety of needs such as hydro-power generation, waste assimilation, navigation, habitat for aquatic life, and expulsion of sea water intrusion. Using the projected need of 150 m3/s for water supply, the instream flow requirement based on hydrological and water quality simulation is estimated to be 467 m3/s in 2010. This suggests that the water sustainability of the East River requires alternative strategies, which may include integrated water resources management, provision of better wastewater treatment, and water and soil conservation.

Assessment of the effects of DEM gridding on the predictions of basin runoff using MIKE SHE and a modelling resolution of 600 m

Summary A 586-km 2 catchment was modelled with the distributed hydrologic model MIKE SHE. Coarse digital elevation models (DEMs) having a 600-m resolution and gridded from a set of elevation points geographically distributed with a much finer resolution were used in the modelling with the purpose of investigating potential effects of the DEM generation methods on (i) model parameter values; (ii) adequacy of model global predictions; and (iii) the evaluation of internal state predictions. To address these aspects, this paper describes the DEM gridding methods, assesses the accuracy of the DEMs and examines systematically the sensitivities of parameter values and predictions of the distributed model with respect to the DEMs. Three types of gridding methods were applied. Methods type I were based on the use of the MIKE SHE interpolation tool (Bilinear algorithm) for processing input elevation data distributed about the periphery of the gridded DEM cells. Input elevation data distributed about the centre of the gridded DEM cells were processed in gridding methods type II. The third type was based on the use of the TOPOGRID algorithm that considers landscape features, such as digitised streams, to improve the drainage structure of the gridded DEMs. A multi-criteria protocol was applied for assessing the elevation quality of DEMs and their suitability for hydrologic purposes. It was found that the quality of the DEM products of the MIKE SHE interpolation tool were poorer. The independent calibration of the assembled hydrologic models revealed (i) important variations of model predictions; and (ii) from average to important variations of effective parameter values, as a function of the different DEMs. A multi-criteria protocol analysing discharge time series, peak flows and piezometric levels showed that model performance is in broad terms in agreement with the elevation and slope quality of the DEMs.

Predicting streamflow response to fire-induced landcover change: Implications of parameter uncertainty in the MIKE SHE model

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model—a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.

Overland flow modeling in a vegetative filter considering non-planar topography and spatial variability of soil hydraulic properties and vegetation density

Summary Vegetative filters are used to remove contaminants from overland flow. Little is known about the impacts of non-planar topography and spatially variable soil hydraulic properties and vegetation density on filter performance. In this study, we developed a protocol for modeling the effects of these quantities on overland flow features which influence greatly the filter efficiency. Two-dimensional overland flow was modeled using the physically based, distributed hydrologic model MIKE SHE. Soil hydraulic properties were represented using spatially variable saturated hydraulic conductivity and a spatially uniform soil–water retention curve. When field measured data and predictions from the uncalibrated model were compared, good agreement was found. The simulated volumetric outflow was within approximately 5% and 25% of the measured outflow at the two areas monitored within the study filter. Non-planar topography significantly impacted overland flow, but accounting for spatially variable roughness and variable soil hydraulic properties had a lesser impact on the two-dimensional overland flow. The volumetric outflow was affected by 36% and 20% because of non-planar topography, 14% and 18% due to variable roughness, and 15% and 16% because of variable soil hydraulic properties for the two grid areas, respectively.

MEASUREMENT AND NUMERICAL ANALYSIS OF HYDROLOGIC CYCLE IN THE MARUGAME PLAIN

In the Marugame plain, recent variation in the hydrologic cycle due to landuse change has posed urgent need to develop new water resources in harmony with the sustainable water cycle. In this paper, measurement of confined and unconfined groundwater and data collection of water uses in the plain were carried out and a numerical analysis of the hydrologic processes for five years including dry and wet years was performed using the MIKE-SHE model, with special emphasis on agricultural water use. It was made clear that the numerical model can fairly reproduce the daily river discharge of the Doki River and the groundwater levels in the plain. And water balance analysis for 1996 showed that the evapotranspiration accounted three-quarters of the annual precipitation and that the domestic water use is heavily dependent on the groundwater and the water introduced through the Kagawa water conveyance channel.

Distributed hydrological modelling in California semi-arid shrublands: MIKE SHE model calibration and uncertainty estimation

The Generalized Likelihood Uncertainty Estimation (GLUE) methodology is used for model calibration, testing and predictive uncertainty estimation in the application of the MIKE SHE hydrologic model for estimating monthly streamflow in a semi-arid shrubland (chaparral) catchment in central California. Monte Carlo simulation is used to randomly generate one thousand parameter sets for a 20-year calibration period encompassing variable climatic and wildfire conditions, from which behavioural (acceptable) MIKE SHE parameter sets are identified and 5% and 95% uncertainty bounds for monthly streamflow are calculated. This group of behavioural parameter sets is subsequently used to predict streamflow and to construct uncertainty bounds for a 12-year test period with climatic and fire characteristics different from those of the calibration period. More than two-thirds of the observations in each period fell within the corresponding uncertainty bounds, suggesting a similar level of model performance in the calibration and test periods. Prediction errors (i.e. observations falling outside the uncertainty bounds) were generally associated with large rainfall and wildfire events and are indicative of deficiencies in model structure, uncertainty in input data, and/or errors in observed streamflow. The effect of uncertainty in remote sensing-based LAI model inputs on the uncertainty associated with MIKE SHE streamflow predictions receives special attention in this work due to the fire-prone nature of the study area and the increasing use of remotely sensed LAI estimates in distributed hydrological modelling applications. Results from MIKE SHE simulations for seven LAI input scenarios (including the baseline LAI sequence used in the model calibration and testing phase of this study) indicate that differences in predictive uncertainty between scenarios are usually less than ±10%. This is evidence that the baseline LAI trajectory is generally appropriate for distributed hydrological modelling of chaparral catchments.