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A new precipitation index-based model, which includes a snow accumulation and melt component, has been developed to simulate hydrology in high latitude catchments. The model couples a point snowmelt model with a current precipitation index ( CPI ) formulation to simulate continuous daily runoff from catchments with seasonal snow cover. A new runoff conversion factor: C T and L f , threshold flow factor Th Q and runoff transformation function Maxbas were introduced into the CPI equation, which converts and transforms the routed daily CPI into daily runoff and maintains the daily base flow in the catchment. The model was developed using twelve sub-arctic boreal catchments located above and below the Arctic Circle in northern Finland, representing a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and produce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. An open-access Excel-based model is provided with this paper for daily runoff simulations. The model can be used to estimate runoff in sub-arctic regions where little data is typically available but significant changes in climate are expected, with considerable shifts in the amount and timing of snowmelt and runoff. [ABSTRACT FROM AUTHOR]

This paper presents a study of the potential for green infrastructure (GI) to restore the predevelopment hydrologic cycle in a semi-arid urban catchment. Simulations of stormwater runoff from a 0.11-km 2 urban catchment in Salt Lake City, Utah, USA for predeveloped (Natural Hydrology, NH), developed (Baseline, BL), and developed with GI (Green Infrastructure, GI) conditions were executed for a one-year period. The study was repeated for a relatively dry year, wet year, and an average year based on precipitation amounts in the year. Bioretention and green roofs were chosen for the GI plan. Results showed that the water budget of the catchment with the GI plan implemented more closely matches the NH water budget compared to the BL scenario, for all three years (dry, wet, average). The BL and GI scenarios showed more significant modifications to the water budget than what has been found by studies in humid climates. Compared to the BL condition, GI annually reduces surface runoff by 35%, 45%, and 43% and restores evapotranspiration by 18%, 19%, and 25% for the dry, average, wet years, respectively. Based on the introduced water budget restoration coefficient (WBRC), the water budget of the study catchment was restored by the GI plan to 90%, 90%, and 82% of the predevelopment state in the dry, average, and wet years, respectively. By comparing the WBRC estimated for other studies, it is further inferred that the water budget is more significantly affected by development and GI restoration in semi-arid than humid climates, but the differences lessen as the precipitation amount increases. [ABSTRACT FROM AUTHOR]

Summary The climate elasticity of runoff is an important indicator that is used to quantify the relationship between changes in runoff and changes in climate variables. It is a function of both climate and catchment characteristics. Recently, Yang and Yang (2011) proposed an analytical derivation of climate elasticity (YY2011), in which a parameter n was used to represent the impact of the catchment characteristics. In China, both climate and catchment characteristics have large spatial variations. To understand the spatial variation of hydrologic response to climate change, this paper divided China into 210 catchments, further calculated the parameter n , and then estimated the climate elasticity and evaluated the contribution of climate change to runoff for each catchment. The results show that n ranges from 0.4 to 3.8 (with a mean of 1.3 and a standard deviation of 0.6), which has a logarithmic relationship with catchment slope; the precipitation elasticity ranges from 1.1 to 4.8 (with a mean of 1.9 and a standard deviation of 0.6), which shows a large regional variation, smaller values (1.1–2.0) mainly appearing in Southern China, the Songhua River basin and the Northwest, and larger values (2.1–4.8) mainly appearing in the Hai River basin, the Liao River basin and the Yellow River basin. In addition, climate contribution to runoff exhibits a large regional variation, the largest positive values (1.1–3.1%/a) occurring in the Northwest, the largest negative values (−1.0 to −0.5%/a) occurring in the Hai River basin and the middle reach of the Yellow River basin. In theory, the YY2011 method is a first-order approximation. The approximation underestimates the precipitation ( P ) contribution to runoff when P increases and overestimates that when P decreases, and the relative error has a median of ∼3% and a maximum of ∼20% when 10% precipitations change in those catchments of China. [ABSTRACT FROM AUTHOR]

Summary: This paper analyses the observed intra-annual variability of the hydrological response in the Blue River basin (Oklahoma, USA) and explores the underlying process controls with the use of the Tsinghua Representative Elementary Watershed (THREW) model, which is a semi-distributed, physically based model. Analysis of rainfall and runoff data at the event scale revealed a seasonal switching pattern of runoff coefficients. Event runoff coefficients in the moderately wet and wet periods (October–April) are consistently higher than those in the dry period (May–September). The switching pattern can be attributed to the higher potential evaporation in the summer season (relative to precipitation), which contributes to a reduction of soil moisture and thus higher initial losses during storm events. This is partly confirmed by the simulation results with the use of the THREW model. However, the results also show that soil drying alone cannot fully explain the sharp drop of the estimated runoff coefficients between spring and summer. This may be indicative that additional abstraction processes may be operative. Three additional abstraction processes are hypothesized as potential explanations, namely, surface depressions, canopy interception and soil cracking. Each of these processes is introduced into the THREW model sequentially, and evaluated in terms of their ability to reproduce various signatures of intra-annual runoff variability, including the switching behavior of event runoff coefficients. Finally, we present simulation results, where all three abstraction processes are included in the THREW model, and the model are recalibrated against the observed data, resulting in improved reproduction of observed streamflows over the baseline results. [ABSTRACT FROM AUTHOR]