Stochastic Rainfall-runoff Model with Explicit Soil Moisture Dynamics

Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF

Framework for Event-based Semidistributed Modeling that Unifies the SCS-CN Method, VIC, PDM, and TOPMODEL

Hydrologists and engineers may choose from a range of semidistributed rainfall-runoff models such as VIC, PDM, and TOPMODEL, all of which predict runoff from a distribution of watershed properties. However, these models are not easily compared to event-based data and are missing ready-to-use analytical expressions that are analogous to the SCS-CN method. The SCS-CN method is an event-based model that describes the runoff response with a rainfall-runoff curve that is a function of the cumulative storm rainfall and antecedent wetness condition. Here we develop an event-based probabilistic storage framework and distill semidistributed models into analytical, event-based expressions for describing the rainfall-runoff response. The event-based versions called VICx, PDMx, and TOPMODELx also are extended with a spatial description of the runoff concept of ‘‘prethreshold’’ and ‘‘threshold-excess’’ runoff, which occur, respectively, before and after infiltration exceeds a storage capacity threshold. For total storm rainfall and antecedent wetness conditions, the resulting ready-to-use analytical expressions define the source areas (fraction of the watershed) that produce runoff by each mechanism. They also define the probability density function (PDF) representing the spatial variability of runoff depths that are cumulative values for the storm duration, and the average unit area runoff, which describes the so-called runoff curve. These new event-based semidistributed models and the traditional SCS-CN method are unified by the same general expression for the runoff curve. Since the general runoff curve may incorporate different model distributions, it may ease the way for relating such distributions to land use, climate, topography, ecology, geology, and other characteristics

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

Understanding runoff processes in a basin is of paramount importance for the effective planning and management of water resources, in particular in data-scarce regions such as the Upper Blue Nile. Hydrological models representing the underlying hydrological processes can predict river discharges from ungauged catchments and allow for an understanding of the rainfall-runoff processes in those catchments. In this paper, such a conceptual process-based hydrological model is developed and applied to the upper Gumara and Gilgel Abay catchments (both located within the Upper Blue Nile Basin, the Lake Tana sub-basin) to study the runoff mechanisms and rainfall-runoff processes in the basin. Topography is considered as a proxy for the variability of most of the catchment characteristics. We divided the catchments into different runoff production areas using topographic criteria. Impermeable surfaces (rock outcrops and hard soil pans, common in the Upper Blue Nile Basin) were considered separately in the conceptual model. Based on model results, it can be inferred that about 65% of the runoff appears in the form of interflow in the Gumara study catchment, and baseflow constitutes the larger proportion of runoff (44-48%) in the Gilgel Abay catchment. Direct runoff represents a smaller fraction of the runoff in both catchments (18-19% for the Gumara, and 20% for the Gilgel Abay) and most of this direct runoff is generated through infiltration excess runoff mechanism from the impermeable rocks or hard soil pans. The study reveals that the hillslopes are recharge areas (sources of interflow and deep percolation) and direct runoff as saturated excess flow prevails from the flat slope areas. Overall, the model study suggests that identifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall-runoff process in the Upper Blue Nile Basin well and yields a useful result for operational management of water resources in this data-scarce region

On the simulation of infiltration- and saturation-excess runoff using radar-based rainfall estimates: Effects of algorithm uncertainty and pixel aggregation

The effects of uncertainty in radar-estimated precipitation input on simulated runoff generation from a medium-sized (100-km2) basin in northern Texas are investigated. The radar-estimated rainfall was derived from Next Generation Weather Radar (NEXRAD) Level II base reflectivity data and was supplemented by ground-based rain-gauge data. Two types of uncertainty in the precipitation estimates are considered: (1) those arising from the transformation of reflectivity to rainfall rate and (2) those due to the spatial and temporal representation of the 'true' rainfall field. The study explicitly differentiates between the response of simulated saturation-excess runoff and infiltration-excess runoff to these uncertainties. The results indicate that infiltration-excess runoff generation is much more sensitive than saturation-excess runoff generation to both types of precipitation uncertainty. Furthermore, significant reductions in infiltration-excess runoff volume occur when the temporal and spatial resolution of the precipitation input is decreased. A method is developed to relate this storm-dependent reduction in runoff volume to the spatial heterogeneity of the highest-intensity rainfall periods during a storm

Description of the hydrochemical regime of the Dnister river (by basic ions)

In this part of the Dniester, water mineralization increases: Dniester - medium (379-428 mg/L); Dniester - lower (425-526 mg/L). Mineralization of the Dniester River water decreases during the spring flood (305-425 mg/L) and increases during the winter low-water period (399-526 mg/L). The average annual ion runoff (Σi) of the Dniester River is 4374.103 tons. For ionic runoff, the same proportion remains for seasons as for water runoff. The ion runoff in the Dniester basin is 60.8 t/km2 per year, which is 2.3 times higher than the ion runoff in the Dnipro basin (26.8 t/km2), but 1.6 times less than in the Danube basin (95.2 t/km2). In general, this is a high indicator of chemical erosion in the river basin

Impacts of model calibration on high-latitude land-surface processes: PILPS 2(e) calibration/validation experiments

In the PILPS 2(e) experiment, the Snow Atmosphere Soil Transfer (SAST) land-surface scheme developed from the Biosphere-Atmosphere Transfer Scheme (BATS) showed difficulty in accurately simulating the patterns and quantities of runoff resulting from heavy snowmelt in the high-latitude Torne-Kalix River basin (shared by Sweden and Finland). This difficulty exposes the model deficiency in runoff formations. After representing subsurface runoff and calibrating the parameters, the accuracy of hydrograph prediction improved substantially. However, even with the accurate precipitation and runoff, the predicted soil moisture and its variation were highly "model-dependent". Knowledge obtained from the experiment is discussed. © 2003 Elsevier Science B.V. All rights reserved

Predictability of seasonal runoff in the Mississippi River basin

Recent advances in climate prediction and remote sensing offer the potential to improve long-lead streamflow forecasts and to provide better land surface state estimates at the time of forecast. We characterize predictability of runoff at seasonal timescales in the Mississippi River basin due to climatic persistence (represented by El Niño-Southern Oscillation and the Arctic Oscillation) and persistence related to the initial land surface state (soil moisture and snow). These climate and land surface state indicators, at varying lead times, are then used in a multiple linear regression to explain the variance of seasonal average runoff. Soil moisture dominates runoff predictability for lead times of 1 1/2 months, except in summer in the western part of the basin, where snow dominates. For the western part of the basin, the land surface state has a stronger predictive capability than climate indicators through leads of two seasons; climate indicators are more important in the east at lead times of one season or greater. Modest winter runoff predictability exists at a lead time of 3 seasons due to both climate and soil moisture, but this is in areas producing little runoff and is therefore of lessened importance. Local summer runoff predictability is limited to the western mountainous areas (generating high runoff) through a lead of 2 seasons. This could be useful to water managers in the western portion of the Mississippi River basin, because it suggests the potential to provide skillful forecast information earlier in the water year than currently used in operational forecasts

Runoff vs. plurality:the effects of the electoral system on local and central government behaviour

Plurality and runoff systems oer very different incentives to parties and coalition of voters, and demand different political strategies from potential candidates and chief executives. Italian mayors and city councils are elected with a different electoral system according to the locality's population, while municipalities are otherwise treated identically in terms of funding and powers. We exploit this institutional feature to test how the presence of different electoral systems affects the central government decisions on grants, and the local government decisions on local taxes. We find evidence that the upper-tier governments favour runoff-elected mayors, and that runoff-elected mayors levy lower taxes. This is broadly consistent with the literature on runoff and plurality rule electoral systems

Using combined prediction models to quantify and visualize stormwater runoff in an urban watershed

Stormwater runoff can transport nutrients, sediments, chemicals, and pathogens to surface waterbodies. Managing runoff is crucial to preserving water quality in rapidly developing urban watersheds like those in Northwest Arkansas. A watershed containing the majority of the University of Arkansas campus was designated as the study area because stormwater from it drains into the West Fork of the White River, designated as an impaired waterbody due to siltation. The project objective was to develop methodology to test existing stormwater drainage infrastructure, identify potential areas of improvement, and estimate potentially contaminated runoff by combining two widely used prediction models. The U.S. Department of Agriculture’s Natural Resource Conservation Service’s curve number (CN) method was used to estimate runoff depths and volumes, while a flow-direction model was created that integrated topography, land use, and stormwater drainage infrastructure in a geographic information system. This study combined the CN and flow-direction models in a single geodatabase to develop flow direction/quantity models. Models were developed for 5-, 10-, 25-, 50-, and 100-year floods and varied by the antecedent moisture content. These models predicted flow directions within existing drainage infrastructure and runoff volumes for each flood, and served as a hypothetical flood analysis model. Results showed that between 24,000 m3 (5-year flood) and 60,000 m3 (100-year flood) of runoff would be transported to the West Fork of the White River. The methodology developed and results generated will help stormwater planners visualize localized runoff, and potentially adapt existing drainage networks to accommodate runoff, prevent flooding and erosion, and improve the quality of runoff entering nearby surface waterbodies

Modelling of hydrological response to climate change in glacierized Central Asian catchments

The arid lowlands of Central Asia are highly dependent on the water supplied by the Tien Shan mountains. Snow and ice storage make large contributions to current runoff, particularly in summer. Two runoff models with different temporal resolutions, HBV-ETH and OEZ, were applied in three glaciated catchments of the Tien Shan mountains. Scenario runs were produced for a climate change caused by the doubling of atmospheric CO2 as predicted by the GISS global circulation model and assuming a 50% reduction of glaciation extent, as well as a complete loss of glaciation. Agreement of the results was best for runs based on 50% glaciation loss, where both models predict an increase in spring and summer runoff compared to current levels. Scenarios for complete loss of glaciation predict an increase in spring runoff levels, followed by lower runoff levels for July and August. Model predictions differ concerning the degree of reduction of late summer runoff. These scenarios are sensitive to model simulation of basin precipitation, as well as to reduction of glaciation extent