Controls on runoff generation and scale-dependence in a distributed hydrologic model

Abstract. Flood-envelope curves (FECs) are useful for constraining the upper limit of possible flood discharges within drainage basins in a particular hydroclimatic region. Their usefulness, however, is limited by their lack of a well-defined recurrence interval. In this study we use radar-derived precipitation estimates to develop an alternative to the FEC method, i.e., the frequency-magnitude-area-curve (FMAC) method that incorporates recurrence intervals. The FMAC method is demonstrated in two well-studied US drainage basins, i.e., the Upper and Lower Colorado River basins (UCRB and LCRB, respectively), using Stage III Next-GenerationRadar (NEXRAD) gridded products and the diffusion-wave flow-routing algorithm. The FMAC method can be applied worldwide using any radar-derived precipitation estimates. In the FMAC method, idealized basins of similar contributing area are grouped together for frequencymagnitude analysis of precipitation intensity. These data are then routed through the idealized drainage basins of different contributing areas, using contributing-area-specific estimates for channel slope and channel width. Our results show that FMACs of precipitation discharge are power-law functions of contributing area with an average exponent of 0.82 ± 0.06 for recurrence intervals from 10 to 500 years. We compare our FMACs to published FECs and find that for wet antecedent-moisture conditions, the 500-year FMAC of flood discharge in the UCRB is on par with the US FEC for contributing areas of ∼ 10 2 to 10 3 km 2 . FMACs of flood discharge for the LCRB exceed the published FEC for the LCRB for contributing areas in the range of ∼ 10 3 to 10 4 km 2 . The FMAC method retains the power of the FEC method for constraining flood hazards in basins that are ungauged or have short flood records, yet it has the added advantage that it includes recurrence-interval information necessary for estimating event probabilities.

Section: Rainfall and Runoff Calculationsmentioning

confidence: 94%

Section: Rainfall and Runoff Calculationsmentioning

confidence: 99%

Section: Rainfall and Runoff Calculationsmentioning

confidence: 99%

See 1 more Smart Citation

Constraining frequency–magnitude–area relationships for rainfall and flood discharges using radar-derived precipitation estimates: example applications in the Upper and Lower Colorado River basins, USA

Orem

Pelletier

2016

“…The coupled framework of the unsaturated and saturated processes results in a set of runoff mechanisms, namely, infiltration-excess runoff (Horton, 1933), saturation excess runoff (Dunne and Black, 1970), groundwater exfiltration (Hursh and Brater, 1941), and perched return flow (Weyman, 1970). Routing of surface flow is achieved via hydrologic overland flow and hydraulic channel routing that uses a kinematic wave approximation (Vivoni et al, 2007a).…”

Section: Distributed Hydrologic Modelmentioning

confidence: 99%

Modeling the distributed effects of forest thinning on the long-term water balance and streamflow extremes for a semi-arid basin in the southwestern US

Moreno

Gupta

White

et al. 2016

Abstract. To achieve water resource sustainability in the water-limited southwestern US, it is critical to understand the potential effects of proposed forest thinning on the hydrology of semi-arid basins, where disturbances to headwater catchments can cause significant changes in the local water balance components and basinwise streamflows. In Arizona, the Four Forest Restoration Initiative (4FRI) is being developed with the goal of restoring 2.4 million acres of ponderosa pine along the Mogollon Rim. Using the physically based, spatially distributed triangulated irregular network (TIN)-based Real-time Integrated Basin Simulator (tRIBS) model, we examine the potential impacts of the 4FRI on the hydrology of Tonto Creek, a basin in the Verde-Tonto-Salt (VTS) system, which provides much of the water supply for the Phoenix metropolitan area. Long-term (20-year) simulations indicate that forest removal can trigger significant shifts in the spatiotemporal patterns of various hydrological components, causing increases in net radiation, surface temperature, wind speed, soil evaporation, groundwater recharge and runoff, at the expense of reductions in interception and shading, transpiration, vadose zone moisture and snow water equivalent, with south-facing slopes being more susceptible to enhanced atmospheric losses. The net effect will likely be increases in mean and maximum streamflow, particularly during El Niño events and the winter months, and chiefly for those scenarios in which soil hydraulic conductivity has been significantly reduced due to thinning operations. In this particular climate, forest thinning can lead to net loss of surface water storage by vegetation and snowpack, increasing the vulnerability of ecosystems and populations to larger and more frequent hydrologic extreme conditions on these semi-arid systems.

“…Kale and Sahoo, 2011;Klar et al, 2008). However, as processes dominating infiltration and surface runoff generation may vary inter-and intra-annually Vivoni et al, 2007) and even within an event (e.g. Silburn and Connolly, 1995), it is important to address potential switches between runoff generation mechanisms in advanced modelling approaches Tian et al, 2012).…”

Section: P Fiener Et Al: Surface Runoff From Arable Fields In Centrmentioning

confidence: 99%

Statistical analysis and modelling of surface runoff from arable fields in central Europe

Fiener

Auerswald²,

Winter³

et al. 2013

Abstract. Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10 % and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58 % of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min −1 , respectively), while RMSE of runoff volume predicted by the curve number model was 50 % higher (7.7 mm). Stone cover, if it exceeded 10 %, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.