Modeling snow hydrology for cold regions remains a problematic aspect of many hydro-environmental models. Temperature-index methods are commonly used and are routinely justified under the auspices that process-based models require too many input data. To test this claim, we used a physical, process-based model to simulate snowmelt at four locations across the conterminous US using energy components estimated from measured daily maximum and minimum temperature, i.e. using only the same data required for temperature-index models. The results showed good agreement between observed and predicted snow water equivalents, average R 2 . 0:9: We duplicated the simulations using a simple temperature-index model best fitted to the data and results were poorer, R 2 , 0:8: At one site we applied the process-based model without substantial parameter estimation, and there were no significant ða ¼ 0:05Þ differences between these results and those obtained using temperature-estimated parameters, despite relatively poorly predicted specific energy budget components ðR 2 , 0:8Þ: These results encourage the use of mechanistic snowmelt modeling approaches in hydrological models, especially in distributed hydrological models for which landscape snow distribution may be controlled by spatially distributed components of the environmental energy budget. q

Abstract:Eective control of nonpoint source pollution from contaminants transported by runo requires information about the source areas of surface runo. Variable source hydrology is widely recognized by hydrologists, yet few methods exist for identifying the saturated areas that generate most runo in humid regions. The Soil Moisture Routing model is a daily water balance model that simulates the hydrology for watersheds with shallow sloping soils. The model combines elevation, soil, and land use data within the geographic information system GRASS, and predicts the spatial distribution of soil moisture, evapotranspiration, saturation-excess overland¯ow (i.e., surface runo), and inter¯ow throughout a watershed. The model was applied to a 170 hectare watershed in the Catskills region of New York State and observed stream¯ow hydrographs and soil moisture measurements were compared to model predictions. Stream¯ow prediction during non-winter periods generally agreed with measured¯ow resulting in an average r 2 of 0 . 73, a standard error of 0 . 01 m 3 /s, and an average Nash-Sutclie eciency R 2 of 0 . 62. Soil moisture predictions showed trends similar to observations with errors on the order of the standard error of measurements. The model results were most accurate for non-winter conditions. The model is currently used for making management decisions for reducing non-point source pollution from manure spread ®elds in the Catskill watersheds which supply New York City's drinking water.

[1] One of the most challenging parameters in hillslope-and watershed-scale, distributed, hydrologic models is the lateral saturated hydraulic conductivity (K s ). In this paper, we present a methodology to determine the hillslope-scale lateral K s above a moderately deep sloping restrictive layer in an 18 Â 35 m hillslope plot using perched water level measurements and drain tile outflow data. The hillslope-scale lateral K s was compared to small-scale K s measured with small soil cores and the Guelph permeameter. Our results show that small-scale K s measurements underestimate the actual hillslope-scale K s . The hillslope-scale K s measurements were 13.7, 4.1, and 3.2 larger than small soil core measurements in the A, B, and E horizons, respectively. We argue that the gap between small-scale and hillslope-scale K s within the same porous medium is foremost a measurement problem. Data analysis provided the K s distribution with depth, showing a sharp decrease in K s within the first 0.1 m of the soil and an exponential decline in K s below 0.1 m. The distribution of K s with depth was best described by a double-exponential relationship. Overall, results indicate the importance of macroporosity, perhaps of biological origin, in determining K s at a hillslope scale.

The location of Costa Rica on the Central American Isthmus creates unique microclimate systems that receive moisture inputs directly from the Caribbean Sea and the Pacific Ocean. In Costa Rica, stable isotope monitoring was conducted by the International Atomic Energy Agency and the World Meteorological Association as part of the worldwide effort entitled Global Network of Isotopes in Precipitation. Sampling campaigns were mainly comprised of monthly-integrated samples during intermittent years from 1990 to 2005. The main goal of this study was to determine spatial and temporal isotopic variations of meteoric waters in Costa Rica using historic records. Samples were grouped in four main regions: Nicoya Peninsula ( 2 H = 6.65 18 O − 0.13; r 2 = 0.86); Pacific Coast ( 2 H = 7.60 18 O + 7.95; r 2 = 0.99); Caribbean Slope ( 2 H = 6.97 18 O + 4.97; r 2 = 0.97); and Central Valley ( 2 H = 7.94 18 O + 10.38; r 2 = 0.98). The water meteoric line for Costa Rica can be defined as  2 H = 7.61 18 O + 7.40 (r 2 = 0.98). The regression of precipitation amount and annual arithmetic means yields a slope of −1.6‰  18 O per 100 mm of rain (r 2 = 0.57) which corresponds with a temperature effect of −0.37‰  18 O/˚C. A strong correlation (r 2 = 0.77) of −2.0‰  18 O per km of elevation was found. Samples within the Nicoya Peninsula and Caribbean lowlands appear to be dominated by evaporation enrichment as shown in d-excess interpolation, especially during the dry months, likely resulting from small precipitation amounts. In the inter-mountainous region of the Central Valley and Pacific slope, complex moisture recycling processes may dominate isotopic variations. Generally, isotopic values tend to be more depleted as the rainy season progresses over the year. Air parcel back trajectories indicate that enriched isotopic compositions both in Turrialba and Monteverde are related to central Caribbean parental moisture and low rainfall intensities. Depleted events appear to be related to high rainfall amounts despite the parental origin of the moisture.

Costa Rica is located on the Central American Isthmus, which receives moisture inputs directly from the Caribbean Sea and the Eastern Pacific Ocean. This location includes unique mountainous and lowland microclimates, but only limited knowledge exists about the impact of relief and regional atmospheric circulation patterns on precipitation origin, transport, and isotopic composition. Therefore, the main scope of this project is to identify the key drivers controlling stable isotope variations in daily-scale precipitation of Costa Rica. The monitoring sites comprise three strategic locations across Costa Rica: Heredia (Central Valley), Turrialba (Caribbean slope), and Caño Seco (South Pacific slope). Sporadic dry season rain is mostly related to isolated enriched events ranging from −5.8‰ to −0.9‰ δ18O. By mid-May, the Intertropical Convergence Zone reaches Costa Rica resulting in a notable depletion in isotope ratios (up to −18.5‰ δ18O). HYSPLIT air mass back trajectories indicate the strong influence on the origin and transport of precipitation of three main moisture transport mechanisms, the Caribbean Low Level Jet, the Colombian Low Level Jet, and localized convection events. Multiple linear regression models constructed based on Random Forests of surface meteorological information and atmospheric sounding profiles suggest that lifted condensation level and surface relative humidity are the main factors controlling isotopic variations. These findings diverge from the recognized 'amount effect' in monthly composite samples across the tropics. Understanding of stable isotope dynamics in tropical precipitation can be used to a) enhance groundwater modeling efforts in ungauged basins where scarcity of long-term monitoring data drastically limit current and future water resources management, b) improve the re-construction of paleoclimatic records in the Central American land bridge, c) calibrate and validate regional circulation models. (Résumé d'auteur

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Abstract:Verification of distributed hydrologic models is rare owing to the lack of spatially detailed field measurements and a common mismatch between the scale at which soil hydraulic properties are measured and the scale of a single modelling unit. In this study, two of the most commonly calibrated parameters, i.e. soil depth and the vertical distribution of lateral saturated hydraulic conductivity K s , were eliminated by a spatially detailed soil characterization and results of a hillslope-scale field experiment. The soil moisture routing (SMR) model, a geographic information system-based hydrologic model, was modified to represent the dominant hydrologic processes for the Palouse region of northern Idaho. Modifications included K s as a double exponential function of depth in a single soil layer, a snow accumulation and melt algorithm, and a simple relationship between storage and perched water depth (PWD) using the drainable porosity. The model was applied to a 2 ha catchment without calibration to measured data. Distributed responses were compared with observed PWD over a 3-year period on a 10 m ð 15 m grid. Integrated responses were compared with observed surface runoff at the catchment outlet. The modified SMR model simulated the PWD fluctuations remarkably well, especially considering the shallow soils in this catchment: a 0Ð20 m error in PWD is equivalent to only a 1Ð6% error in predicted soil moisture content. Simulations also captured PWD fluctuations during a year with high spatial variability of snow accumulation and snowmelt rates at upslope, mid-slope, and toe slope positions with errors as low as 0Ð09 m, 0Ð12 m, and 0Ð12 m respectively. Errors in distributed and integrated model simulations were attributed mostly to misrepresentation of rain events and snowmelt timing problems. In one location in the catchment, simulated PWD was consistently greater than observed PWD, indicating a localized recharge zone, which was not identified by the soil morphological survey.