Distributed Hydrology Soil Vegetation Model Research Articles

Distributed hydrological modeling of a micro-scale rainforest watershed in Amazonia: Model evaluation and advances in calibration using the new HAND terrain model

Summary Three sections of the Asu catchment, which is located within the Cuieiras Reservation 80 km northwest of Manaus in Central Amazonia, Brazil, were gauged to create nested catchments of the first (0.95 km 2 ), second (6.58 km 2 ) and third (12.43 km 2 ) Strahler orders. As the Cuieiras reserve contains pristine tropical rainforest, hydrological data collected in these catchments offers an opportunity to test the Distributed Hydrology Soil Vegetation Model’s (DHSVM) ability to simulate hydrological responses, and to represent the spatial distribution of hydrological phenomena such as evapotranspiration, soil moisture and water table depth. Digital Elevation Model (DEM) data were obtained from the Shuttle Radar Topography Mission (SRTM) data. We used a novel approach to produce high resolution (30 m) soil and vegetation maps that enabled a representative set of relevant parameters to be acquired. These soil and vegetation maps were derived from a hydrologically normalized DEM through the HAND (Height Above the Nearest Drainage) technique, a new type of terrain model procedure. The DHSVM model was calibrated and validated using the second order watershed. To test the model’s ability to represent processes at different spatial scales, the parameter set derived from the calibration was used to simulate the discharge of the first and third order streams. Model simulations of soil moisture, groundwater levels and discharge were compared with observed data and exhibited satisfactory performance overall, with the exceptions of the predicted water table depth and the underestimation of peak flows during the wet season. The results from these DHSVM runs indicate that the model is applicable to tropical forests environments (equatorial climates, lowland watersheds with deep soil), which are quite distinct from the environments for which the model was developed (temperate climates, mountainous watersheds with shallow soil). The study also demonstrated that the HAND terrain model is a useful tool for representing the spatial distributions of key hydrological parameters.

Distributed temperature-index snowmelt modelling for forested catchments

► We adapt extended temperature-index snowmelt algorithms for forested catchments. ► A simple model for canopy interception reasonably predicts snow accumulation. ► Extended temperature-index algorithms can be as accurate as an energy balance model. ► Accounting for cold-content was required to realize the increased performance. ► One algorithm is also capable of simulating the diurnal cycle of meltwater outflow. This work was motivated by the need to understand the hydrologic consequences of rapid and widespread forest disturbance to assist forest management and operational forecasting. The objective was to compare three extended temperature-index-based melt models to a basic temperature-index model, as well as to the physically based snow model in the Distributed Hydrology-Soil-Vegetation Model (DHSVM). One model uses ad hoc parameterizations to represent the variation of the melt factor with slope-aspect, forest cover and time of year. The other two incorporate either potential direct or measured solar radiation; they were originally developed for open sites and were adapted to account for the effects of forest cover. The models were calibrated and tested using lysimeter data and spatially distributed snow surveys conducted at the Cotton Creek Experimental Watershed located in southeast British Columbia, Canada. A model for canopy interception that included a maximum canopy storage and a fixed sublimation rate provided reasonable predictions of peak snow accumulation. Accounting for cold content in the upper layer of a two-layer snowpack model was required to realize the increased predictive performance of the extended temperature-index melt models, compared to the most basic model. The model that incorporated measured solar radiation provided the best performance, and was almost as accurate as the DHSVM snow model. The model that uses potential direct radiation also performed well in spatial testing and, in addition, closely matched day-time highs and night-time lows of the measured lysimeter outflow. The model with ad hoc representations did not perform as well as the other extended temperature-index models outside the calibration period. Spatially distributed snowpack measurements assisted in constraining the parameters in the extended temperature-index models. Further research should test the extended temperature-index melt models at the catchment scale, particularly in catchments where there have been rapid and well documented changes in forest cover.

Hydrologic response of a Hawaiian watershed to future climate change scenarios

AbstractThe impact of potential future climate change scenarios on streamflow and evapotranspiration (ET) in a mountainous Hawaii watershed was studied using the distributed hydrology soil vegetation model (DHSVM). The hydrologic response of the watershed was simulated for 43 years for different levels of atmospheric CO2 (330, 550, 710 and 970 ppm), temperature (+1.1 and + 6.4 °C) and precipitation (±5%, ±10% and ±20%) on the basis of the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under current, B1, A1B1 and A1F1 emission scenarios. Vegetation leaf conductance and leaf area index were modified to reflect the increase in CO2 concentration. The relative departure of streamflow and ET from their levels during the reference scenarios was calculated on a monthly and annual basis. Results of this study indicate that the streamflow and ET are less sensitive to changes in temperature compared with changes in precipitation. However, temperature increase coupled with precipitation showed significant effect on ET and streamflow. Changes in leaf conductance and leaf area index with increasing CO2 concentration under A1F1 scenario had a significant effect on ET and subsequently on streamflow. Evapotranspiration is less sensitive than streamflow for a similar level of change in precipitation. On the basis of a range of climate change scenarios, DHSVM predicted a change in ET by ±10% and streamflow between −51% and 90%. From the six ensemble mean scenarios for AR4 A1B, simulations suggest reduction in streamflow by 6.7% to 17.2%. These reductions would produce severe impact on water availability in the region. Copyright © 2011 John Wiley & Sons, Ltd.

Road runoff and sediment sampling for determining road sediment yield at the watershed scale

In this study, we demonstrate that watershed-scale estimates of road sediment production are improved if field measurements of road runoff and sediment production are used in the analysis. We used several techniques to spatially extrapolate measurements of road runoff and sampled sediment: comprehensive road runoff measurements, runoff estimates derived from the Distributed Hydrology Soil Vegetation Model (DHSVM), and adjustment of the road erosion models WARSEM and SEDMODL2.The sediment yield for the Oak Creek, Oregon, road network based on measured road runoff and sediment was 6.5 tons/year. When DHSVM was used to simulate road runoff, the estimated sediment from roads was similar, 6.9 tons/years. The road sediment production estimated by SEDMODL2 and WARSEM, adjusted with field-measured road runoff and sediment, was 28% and 34% less, respectively, than using the models with the default parameters. When applied to a road network in commercial forest land with frequent road use, the sediment yield estimated by SEDMODL2 and WARSEM without adjustment from field measurements was 480% and 610% higher, respectively, than with adjustments. We found that measuring runoff and sediment from one large storm event (≥1 year recurrence) provided a statistically significant relationship with the annual sediment yield.

Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai‘i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at Mākaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2 h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather data generation and disaggregation methods were concentrated in a few Hawaiian watersheds, the results presented can be used to similar mountainous location settings, as well as any specific locations aimed at furthering the site-specific performance evaluation of these tested models.

Lumped parameter sensitivity analysis of a distributed hydrological model within tropical and temperate catchments

AbstractParameter sensitivity of the Distributed Hydrology‐Soil‐Vegetation Model (DHSVM) was studied in two contrasting environments: (1) Pang Khum Experimental Watershed (PKEW) in tropical northern Thailand; and (2) Cedar River basin (CRB) in Washington State of the temperate US Pacific Northwest. The analysis shows that for both basins, the most sensitive soil parameters were porosity, lateral saturated hydraulic conductivity, and the exponential decrease rate of lateral saturated hydraulic conductivity with soil depth. The most sensitive vegetation parameters were leaf area index, vegetation height, vapour pressure deficit, minimum stomatal resistance (for both grassland and forest scenarios), hemisphere fractional coverage, overstory fractional coverage, and trunk space (for the forest scenario only). Parameter sensitivity was basin‐specific, with the humid, temperate CRB being more influenced by vegetation parameters, while tropical PKEW was more influenced by soil properties. Increases and decreases in parameter values resulted in opposite and unequal changes in bias and root mean square error (RMSE), indicating the non‐linearity of physical process represented in the hydrological model. Copyright © 2011 John Wiley & Sons, Ltd.

Modelling hydrological processes influenced by soil, rock and vegetation in a small karst basin of southwest China

AbstractHydrological processes in karst basins are controlled by permeable multimedia, consisting of soil pores, epikarst fractures, and underground conduits. Distributed modelling of hydrological dynamics in such heterogeneous hydrogeological conditions is a challenging task. Basing on the multilayer structure of the distributed hydrology‐soil‐vegetation model (DHSVM), a distributed hydrological model for a karst basin was developed by integrating mathematical routings of porous Darcy flow, fissure flow and underground channel flow. Specifically, infiltration and saturated flow movement within epikarst fractures are expressed by the ‘cubic law’ equation which is associated with fractural width, direction, and spacing. A small karst basin located in Guizhou province of southwest China was selected for this hydrological simulation. The model parameters were determined on the basis of field measurement and calibrated against the observed soil moisture contents, vegetation interception, surface runoff, and underground flow discharges from the basin outlet. The results show that due to high permeability of the epikarst zone, a significant amount of surface runoff is only generated after heavy rainfall events during the wet season. Rock exposure and the epikarst zone significantly increase flood discharge and decrease evapotranspiration (ET) loss; the peak flood discharge is directly proportional to the size of the aperture. Distribution of soil moisture content (SMC) primarily depends on topographic variations just after a heavy rainfall, while SMC and actual ET are dominated by land cover after a period of consecutive non‐rainfall days. The new model was able to capture the sharp increase and decrease of the underground streamflow hydrograph, and as such can be used to investigate hydrological effects in such rock features and land covers. Copyright © 2011 John Wiley & Sons, Ltd.

Effects of mid-twenty-first century climate and land cover change on the hydrology of the Puget Sound basin, Washington

The distributed hydrology–soil–vegetation model (DHSVM) was used to study the potential impacts of projected future land cover and climate change on the hydrology of the Puget Sound basin, Washington, in the mid-twenty-first century. A 60-year climate model output, archived for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), was statistically downscaled and used as input to DHSVM. From the DHSVM output, we extracted multi-decadal averages of seasonal streamflow, annual maximum flow, snow water equivalent (SWE), and evapotranspiration centred around 2030 and 2050. Future land cover was represented by a 2027 projection, which was extended to 2050, and DHSVM was run (with current climate) for these future land cover projections. In general, the climate change signal alone on sub-basin streamflow was evidenced primarily through changes in the timing of winter and spring runoff, and slight increases in the annual runoff. Runoff changes in the uplands were attributable both to climate (increased winter precipitation, less snow) and land cover change (mostly reduced vegetation maturity). The most climatically sensitive parts of the uplands were in areas where the current winter precipitation is in the rain–snow transition zone. Changes in land cover were generally more important than climate change in the lowlands, where a substantial change to more urbanized land use and increased runoff was predicted. Both the annual total and seasonal distribution of freshwater flux to Puget Sound are more sensitive to climate change impacts than to land cover change, primarily because most of the runoff originates in the uplands. Both climate and land cover change slightly increase the annual freshwater flux to Puget Sound. Changes in the seasonal distribution of freshwater flux are mostly related to climate change, and consist of double-digit increases in winter flows and decreases in summer and fall flows. Copyright © 2010 John Wiley & Sons, Ltd.

Uncertainty assessment of forest road modeling with the Distributed Hydrology Soil Vegetation Model (DHSVM)

We used a generalized likelihood uncertainty estimation procedure with the Distributed Hydrology Soil Vegetation Model (DHSVM) for two streamflow and 11 road ditchflow locations. We observed considerable uncertainty in DHSVM simulations of forest road and stream runoff. The accuracy of simulations decreased as the size of the area modeled decreased. For streamflow, 44% of attempted model structures exceeded a 0.5 Nash–Sutcliffe efficiency threshold for a 630 ha catchment; 12% of attempted model structures exceeded a 0.5 Nash–Sutcliffe efficiency threshold for a 55 ha catchment. DHSVM simulations produced behavioral model structures for only six of the 11 road ditchflow sites (<10 ha). Cumulative distribution functions of parameter values did not indicate specific parameter ranges of parameter values across all locations, indicating that parameter values in DHSVM are influenced by their interaction with other parameters. The sensitivity of parameters and the range of that sensitivity varied across simulations of road ditchflow and streamflow. DHSVM simulations for two streamflow locations varied outside the uncertainty bounds for 10%–22% of storm volumes and 12%–22% of peak flows, respectively. Twenty-eight percent to 52% of storm volumes and 28%–48% of peak flows were outside the uncertainty bounds for the six road ditchflow locations.

Variability of snow water equivalent and snow energetics across a large catchment subject to Mountain Pine Beetle infestation and rapid salvage logging

Summary This study examines the effect on stand and catchment scale snow processes due to widespread forest disturbance by the Mountain Pine Beetle (MPB; Dendroctonus ponderosae ) infestation, for the 1570 km 2 Baker Creek catchment in the B.C. interior where all healthy mature lodgepole pine ( Pinus contorta ) stands which dominated the catchment up until 2000 have since died or been salvage logged. Measurements in 2008 and 2009 indicate that this net canopy reduction has reduced peak snowpack and melt rate differences between remaining stands (including large clearcuts, younger regenerating stands and dead mature pine stands), relative to a healthy forest canopy with smaller clearcuts. The Distributed Hydrology Soil Vegetation Model (DHSVM) was calibrated and run at 200 m resolution across the catchment, and simulated snowmelt rates and snow-covered area compared relatively well to distributed satellite or ground-based measurements. Snowpack and ablation rates were 10–20% higher during the 2008 and 2009 winters than when running the model for the pre-MPB landscape in 2000 using the same input meteorological data, resulting in almost no difference in the snowcover period. A greater snowpack volume which enters the stream network faster inevitably has implications for streamflows, flood risks and water resources, and these are assessed during the next stage of this research project.

Assimilation of ASAR data with a hydrologic and semi-empirical backscattering coupled model to estimate soil moisture

The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling. However, there is much uncertainty in the assimilation process, which affects the assimilation results. This research developed a one-dimensional soil moisture assimilation scheme based on the Ensemble Kalman Filter (EnKF) and Genetic Algorithm (GA). A two-dimensional hydrologic model—Distributed Hydrology-Soil-Vegetation Model (DHSVM) was coupled with a semi-empirical backscattering model (Oh). The Advanced Synthetic Aperture Radar (ASAR) data were assimilated with this coupled model and the field observation data were used to validate this scheme in the soil moisture assimilation experiment. In order to improve the assimilation results, a cost function was set up based on the distance between the simulated backscattering coefficient from the coupled model and the observed backscattering coefficient from ASAR. The EnKF and GA were used to re-initialize and re-parameterize the simulation process, respectively. The assimilation results were compared with the free-run simulations from hydrologic model and the field observation data. The results obtained indicate that this assimilation scheme is practical and it can improve the accuracy of soil moisture estimation significantly.

Climate change impacts on water management in the Puget Sound region, Washington State, USA

Climate change is projected to result, on average, in earlier snowmelt and reduced summer flows in the Pacific Northwest, patterns not well represented in historical observations used in water planning. We evaluate the sensitivities of water supply systems in the Puget Sound basin cities of Everett, Seattle, and Tacoma to historical and projected future streamflow variability and water demands. We simulate streamflow for the 2020s, 2040s, and 2080s using the distributed hydrology–soil–vegetation model (DHSVM), driven by downscaled ensembles of climate simulations archived from the 2007 IPCC Fourth Assessment Report. We use these streamflow predictions as inputs to reservoir system models for the three water supply systems. Over the next century, under average conditions all systems are projected to experience declines and eventual disappearance of the springtime snowmelt peak. How these shifts affect management depends on physical characteristics, operating objectives, and the adaptive capacity of each system. Without adaptations, average seasonal drawdown of reservoir storage is projected to increase in all three systems throughout the 21st century. Reliability of all systems in the absence of demand increases is robust through the 2020s however, and remains above 98% for Seattle and Everett in the 2040s and 2080s. With demand increases, however, reliability of the systems in their current configurations and with current operating policies progressively declines through the century.

A snowmelt runoff forecasting model coupling WRF and DHSVM

Abstract. This study linked the Weather Research and Forecasting (WRF) modelling system and the Distributed Hydrology Soil Vegetation Model (DHSVM) to forecast snowmelt runoff. The study area was the 800 km2 Juntanghu watershed of the northern slopes of Tianshan Mountain Range. This paper investigated snowmelt runoff forecasting models suitable for meso-microscale application. In this study, a limited-region 24-h Numeric Weather Forecasting System was formulated using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. Using the WRF forecasts, the DHSVM hydrological model was used to predict 24 h snowmelt runoff at the outlet of the Juntanghu watershed. Forecasted results showed a good similarity to the observed data, and the average relative error of maximum runoff simulation was less than 15%. The results demonstrate the potential of using a meso-microscale snowmelt runoff forecasting model for forecasting floods. The model provides a longer forecast period compared with traditional models such as those based on rain gauges or statistical forecasting.

Parameters optimization on DHSVM model based on a genetic algorithm

Due to the multiplicity of factors including weather, the underlying surface and human activities, the complexity of parameter optimization for a distributed hydrological model of a watershed land surface goes far beyond the capability of traditional optimization methods. The genetic algorithm is a new attempt to find a solution to this problem. A genetic algorithm design on the Distributed-Hydrology-Soil-Vegetation model (DHSVM) parameter optimization is illustrated in this paper by defining the encoding method, designing the fitness value function, devising the genetic operators, selecting the arithmetic parameters and identifying the arithmetic termination conditions. Finally, a case study of the optimization method is implemented on the Lushi Watershed of the Yellow River Basin and achieves satisfactory results of parameter estimation. The result shows that the genetic algorithm is feasible in optimizing parameters of the DHSVM model.

Análise de Sensibilidade do Modelo Hidrológico Distribuído DHSVM aos Parâmetros de Vegetação

The Distributed Hydrology Soil Vegetation Model (DHSVM) was applied to the Bocaina watershed, located in Serra do Mar in Sao Paulo State, Brazil. Hydrological modeling of this region is of great strategic importance both economically, due to its position connecting important cities to the Atlantic Ocean, and environmentally, due to areas of remaining native forest called Mata Atlântica(Atlantic Forest). Distributed hydrologic al models have many physi- cal parameters, and knowing the most relevant ones in simulated outflows may guide future investments on expe- rimental research to determine them, and may also indicate the most relevant for calibration. Among the vegetation parameters, the model presented greater sensitivity to the variations of vapor pressure deficit, minimum stomatal resistance, leaf area index and vegetation height

Hydrologic prediction for urban watersheds with the Distributed Hydrology–Soil–Vegetation Model

AbstractSome relatively straightforward modifications to the Distributed Hydrology–Soil–Vegetation Model (DHSVM) are described that allow it to represent urban hydrological processes. In the modified model, precipitation that falls on impervious surfaces becomes surface runoff, and a spatially varying (depending on land cover) fraction of surface runoff is connected directly to the stream channel, with the remainder stored and slowly released to represent the effects of stormwater detention. The model was evaluated through application to Springbrook Creek watershed in a partially urbanized area of King County, Washington. With calibration, the modified DHSVM simulates hourly streamflow from these urbanized catchments quite well. It is also shown how the revised model can be used to study the effects of continuing urbanization in the much larger Puget Sound basin. Model simulations confirm many previous studies in showing that urbanization increases peak flows and their frequency, and decreases peak flow lag times. The results show that the urbanization parameterizations for DHSVM facilitate use of the model for prediction and/or reconstruction of a range of historic and future changes in land cover that will accompany urbanization as well as other forms of vegetation change. Copyright © 2008 John Wiley & Sons, Ltd.

The roles of roads and agricultural land use in altering hydrological processes in Nam Mae Rim watershed, northern Thailand

AbstractThe distributed hydrology soil vegetation model (DHSVM) is applied in the 107 km2 Nam Mae Rim watershed (NMRW) in northern Thailand. Simulations using land cover scenarios for 1989 and 2002, extreme deforestation, and forest, each run with and without roads, show that roads have very small effects on the mean water fluxes, but significantly increase peak flows for all land cover scenarios. The magnitude of the road effect on peak flow depends on the land cover context in which the roads are placed. Roads have the smallest effect on peaks within the extreme deforestation scenario, and affect mainly the smallest peaks in the two homogeneous land cover scenarios (forest and extreme deforestation). Roads have the largest effect on peaks within the heterogeneous landscapes of the two historical land cover scenarios (1989 and 2002). This result indicates that, by conveying surface flow quickly to the stream, roads within a fragmented landscape are especially important in converting greater amounts of overland flow into higher peak flows. Without roads, the patchy land cover pattern buffers the impacts of the scattered overland flow source areas and limits increases in peak flows.The combined effects of land cover and roads are examined in comparison with forest. The 1989 and 2002 land cover patterns result in relatively small changes in the mean annual water balance, but with some significant changes in the seasonal distribution of fluxes. Streamflow is lower in the late wet season and higher in the dry season for the 1989 and 2002 scenarios compared with forest. Conversion from forest to any of the other land cover scenarios results in higher dry season evapotranspiration (ET) and lower wet season ET. The extreme deforestation scenario results in much lower wet season ET and much higher annual streamflow, but little change in dry season streamflow, in comparison with forest. Copyright © 2008 John Wiley & Sons, Ltd.

Effects of landuse change on the hydrologic regime of the Mae Chaem river basin, NW Thailand

Summary Conflicts between upland shifting cultivation, upland commercial crops, and lowland irrigated agriculture cause water resource tension in the Mae Chaem watershed in Chiang Mai, Thailand. In this paper, we assess hydrologic regimes of the Mae Chaem River with landuse change. Three plausible future forest-to-crop expansion scenarios and a scenario of crop-to-forest reversal were developed based on the landcover transition from 1989 to 2000, with emphasis on influences of elevation bands and irrigation diversion. Basin hydrologic responses were simulated using the Distributed Hydrology Soil Vegetation Model (DHSVM). Meteorological data from six weather stations inside and adjacent to the Mae Chaem watershed during the period 1993–2000 were the climate inputs. Computed stream flow was compared to observed discharge at Ban Mae Mu gauge on Mae Mu river, Ban Mae Suk gauge on Mae Suk river, and at Kaeng Ob Luang, located downstream from the district town in Mae Chaem. With current assumptions, expansion of highland crop fields led to slightly higher regulated annual and wet-season water yields compared to similar expansion in the lowland–midland zone. Actual downstream water availability was sensitive to irrigation diversion. This modeling approach can be a useful tool for water allocation for small watersheds undergoing rapid commercialization, because it alerts land managers to the potential range of water supply in wet and dry seasons, and provides information on spatial distribution of basin hydrologic components.

A spatially distributed model for the dynamic prediction of sediment erosion and transport in mountainous forested watersheds

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment model that represents the main sources of sediment generation in forested environments (mass wasting, hillslope erosion, and road surface erosion) within the distributed hydrology‐soil‐vegetation model (DHSVM) environment. The model produces slope failures on the basis of a factor‐of‐safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule‐based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. A simple channel routing scheme is implemented to predict basin sediment yield. We demonstrate through an initial application of this model to the Rainy Creek catchment, a tributary of the Wenatchee River, which drains the east slopes of the Cascade Mountains, that the model produces plausible sediment yield and ratios of landsliding and surface erosion when compared to published rates for similar catchments in the Pacific Northwest. A road removal scenario and a basin‐wide fire scenario are both evaluated with the model.

Use of the distributed hydrology soil vegetation model to study road effects on hydrological processes in Pang Khum Experimental Watershed, northern Thailand

The distributed-hydrology-soil-vegetation model (DHSVM) is applied in the mountainous 94 ha Pang Khum Experimental Watershed (PKEW), northern Thailand. Climate data from August 1997 to January 2001 are used to warm up, calibrate and validate DHSVM with the existing road network explicitly represented in the model. Calibrated and tested variables are soil moisture and streamflow. The model is subsequently run again without the road, otherwise keeping parameter settings and forcing data the same. Model results with and without roads are used to study road effects on evapotranspiration, soil moisture, depth to water table, and stream discharge. Application of DHSVM had mixed results. The model simulated soil moisture at four measurement sites and three depths very well. Streamflow was adequately estimated in only 2 of the 3 years tested, including the calibration year. The quality of the streamflow simulation may have been reduced because of year-to-year changes in land cover or water diversions not represented in the model. Model results show that the road causes relatively small changes to averaged monthly total evapotranspiration and stream discharge in PKEW during the 3-year study period due to the low road density. Small changes in soil moisture and depth to water table occurred adjacent to and down slope of roads in PKEW. Roads increase peak flows in simulations by 3, 12, and 34%, for peak flows of less than 200, 200–800, and greater than 800 m 3 h −1, respectively.