scholarly journals Modelling subsurface storm flow with the Representative Elementary Watershed (REW) approach: application to the Alzette River Basin

2006 ◽  
Vol 3 (1) ◽  
pp. 229-270 ◽  
Author(s):  
G. P. Zhang ◽  
H. H. G. Savenije ◽  
F. Fenicia ◽  
L. Pfister
Keyword(s):  
River Basin ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Catchment Scale ◽  
Model Code ◽  
Main River ◽  
Storm Flow ◽  
Rainfall Runoff Model ◽  
Table Data ◽  
Runoff Model

Abstract. A new domain, the macropore domain, for describing subsurface storm flow has been introduced to the Representative Elementary Watershed (REW) approach. The mass balance equations have been reformulated and the closure relations associated with subsurface storm flow have been developed. The model code, REWASH, has been revised accordingly. With the revised REWASH, a rainfall-runoff model has been built for the Hesperange catchment, a sub-catchment of the Alzette River Basin. This meso-scale catchment is characterised by fast catchment response to precipitation and subsurface storm flow is one of the dominant runoff generation processes. The model has been evaluated by a multi-criteria approach using both discharge and groundwater table data measured at various locations in the study site. It is demonstrated that subsurface storm flow contributes considerably to stream flow in the study area. Simulation results show that discharges measured along the main river course are well simulated and groundwater dynamics is well captured, suggesting that the model is a useful tool for catchment-scale hydrological analysis.

scholarly journals Modelling subsurface storm flow with the Representative Elementary Watershed (REW) approach: application to the Alzette River Basin

2006 ◽  
Vol 10 (6) ◽  
pp. 937-955 ◽  
Author(s):  
G. P. Zhang ◽  
H. H. G. Savenije ◽  
F. Fenicia ◽  
L. Pfister
Keyword(s):  
River Basin ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Catchment Scale ◽  
Model Code ◽  
Main River ◽  
Storm Flow ◽  
Rainfall Runoff Model ◽  
Table Data ◽  
Runoff Model

Abstract. A new domain, the macropore domain describing subsurface storm flow, has been introduced to the Representative Elementary Watershed (REW) approach. The mass balance equations have been reformulated and the closure relations associated with subsurface storm flow have been developed. The model code, REWASH, has been revised accordingly. With the revised REWASH, a rainfall-runoff model has been built for the Hesperange catchment, a sub-catchment of the Alzette River Basin. This meso-scale catchment is characterised by fast catchment response to precipitation, and subsurface storm flow is one of the dominant runoff generation processes. The model has been evaluated by a multi-criteria approach using both discharge and groundwater table data measured at various locations in the study site. It is demonstrated that subsurface storm flow contributes considerably to stream flow in the study area. Simulation results show that discharges measured along the main river course are well simulated and groundwater dynamics is well captured, suggesting that the model is a useful tool for catchment-scale hydrological analysis.

Combining static and portable Cosmic Ray Neutron Sensor (CRNS) data to assess catchment scale heterogeneity in soil water content and implications for runoff generation

2021 ◽  
Author(s):  
Katya Dimitrova Petrova ◽  
Rafael Rosolem ◽  
Chris Soulsby ◽  
Mark Wilkinson ◽  
Allan Lilly ◽  
...  
Keyword(s):  
Soil Water ◽  
Model Calibration ◽  
Cosmic Ray ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Catchment Scale ◽  
Near Surface ◽  
Mineral Soils ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>Soil water content (SWC) dynamics can strongly influence catchment runoff generation processes. Knowledge about the amount and spatiotemporal distribution of SWC at the catchment scale can be useful for constraining and evaluating rainfall-runoff models.  While it is still challenging to obtain catchment scale-representative measurements of SWC, recent advances in cosmic ray neutron sensor (CRNS) technology have provided opportunities to obtain hectare scale data on SWC. Here we present a new method for obtaining spatially variable near-surface SWC by combining a high temporal resolution static CRNS sensor with ‘snapshot’ surveys using a portable CRNS. We also explored the role of these soil water storage data for catchment in rainfall-runoff generation models. We used ~4-years of near-surface SWC data from a static CRNS located in a humid mixed-agricultural catchment (~10km<sup>2</sup>) in Scotland. These data were complemented with at least three ‘snapshot’ portable CRNS surveys in each of the four main soil-land use (SLU) units in the catchment to produce SWC timeseries for each of these units. Two SLU units involved rotational crops under poorly or imperfectly draining mineral soils; one SLU unit typically supports livestock farming on freely draining mineral soils and the fourth, moorland on organic-rich soils.  While the moorland SLU unit on organic soils had the greatest difference in SWC dynamics under the static CRNS and other SLUs, we also found subtle SWC differences between mineral soil SLU units under different agricultural management. We then evaluated the additional information generated by the combined CRNS method in a rainfall-runoff model (HBV-light) calibration of dynamic catchment storage. For the purpose, we used areal weighted SLU SWC timeseries and compared the model calibration to that using the static CRNS alone. In this case, differences were marginal and model efficiencies similar, suggesting that static CRNS data from a landscape-representative location may be sufficient to inform rainfall-runoff model calibration at the catchment scale.  However, this may depend on model structure and the degree to which SWC dynamics vary within the landscape. This study demonstrated the potential of expanding the information value of permanently installed CRNS sensors using portable CRNS surveys in the context of humid mixed-agricultural environment, although testing in different environments would be required to evaluate wider applicability.</p>

Macropore domination in runoff generation process: A case study by hydrological modelling in Hilly Watersheds of Koshi River Basin, Himalaya

2021 ◽  
Author(s):  
Suman Kumar Padhee ◽  
Subashisa Dutta
Keyword(s):  
River Basin ◽  
Hydrological Process ◽  
Generation Process ◽  
Watershed Scale ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Calibration And Validation ◽  
Koshi River Basin ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>A recent initiative by the hydrologic community identified processes that control hillslope-riparian-stream-groundwater interactions as one of the major unsolved scientific problems in Hydrology. It is a long-time argument among hydrologists whether to eliminate the minor details from field-based costing a lot of time, effort, and resources to understand the hydrological process in watershed scale. The modelling approaches are helpful is these cases by focusing on the dominant controllers and might/might'nt bypassing the implications from minor details. In this work, a conceptual semi-distributed rainfall-runoff model for hilly watersheds is used with satellite-based hydrometeorological inputs to parameterize, and thus understand by calibration and validation, at Koshi River Basin, a partly hilly watershed in Himalaya. The semi-distributed model is operated by dividing the river basin into small grids of around 1km<sup>2</sup>, each representing a micro-watershed. Majority of the model concept is drawn from fill and spill approach from previous literature, observations from plot-scale hillslope experiments, and macropore characterization from dye-tracer experiments, which are upscaled at micro-watershed scale. The parameterization in the rainfall-runoff model includes the daily average variables namely, threshold for runoff generation (<em>T</em>), gradient of runoff generation rate (<em>S</em>), saturated hydraulic conductivity for hillslope aquifers (<em>Ksat</em>), and aquifer thickness limit (<em>D</em>). Variable ranges of these parameters were simulated to find the best values (<em>T</em> = 1±0.25cm; <em>S</em> = 0.6 – 0.1; <em>Ksat</em> ≈ 10<sup>5</sup> – 10<sup>10</sup> times original Ksat; and <em>D </em>= 1m). These ranges resulted in over (NSE = 0.6; R<sup>2</sup> = 0.65) during calibration and validation for daily flow volume at the outlet. In these simulations, the <em>Ksat </em>multiplied with factors at several orders higher scale and producing good NSE values shows domination of preferential pathways in runoff generation process. This might represent a flow similar to that of overland flow affecting the surface runoff volume at river basin scale. This model could be used for water budgeting studies in hilly watersheds where several hillslopes dominated by macropores are present.</p>

scholarly journals A Modified IHACRES Rainfall–Runoff Model for Predicting Hydrologic Response of a River Basin System with a Relevant Groundwater Component

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 24
Author(s):  
Iolanda Borzì ◽  
Brunella Bonaccorso ◽  
Aldo Fiori
Keyword(s):  
River Basin ◽  
Slow Component ◽  
Temperature Data ◽  
Continuous Series ◽  
Effective Rainfall ◽  
Rainfall Runoff ◽  
Aquifer Recharge ◽  
Daily Streamflow ◽  
Rainfall Runoff Model ◽  
Runoff Model

A flow regime can be broadly categorized as either perennial, intermittent, or ephemeral, depending on whether the streamflow is continuous all year round, or ceasing for weeks or months each year. Various conceptual models are needed to capture the behavior of these different flow regimes, which reflect differences in the stream–groundwater hydrologic connection. As the hydrologic connection becomes more transient and a catchment’s runoff response more nonlinear, such as for intermittent streams, the need for explicit representation of the groundwater increases. In the present study, we investigated the connection between the Northern Etna groundwater system and the Alcantara River basin in Sicily, which is intermittent in the upstream, and perennial since the midstream, due to groundwater resurgence. To this end, we apply a modified version of IHACRES rainfall–runoff model, whose input data are a continuous series of concurrent daily streamflow, rainfall and temperature data. The structure of the model includes three different modules: (1) a nonlinear loss module that transforms precipitation to effective rainfall by considering the influence of temperature; (2) a linear module based on the classical convolution between effective rainfall and the unit hydrograph which is able to simulate the quick component of the runoff; and (3) a second nonlinear module that simulates the slow component of the runoff and that feeds the groundwater storage. From the sum of the quick and slow components (except for groundwater losses, representing the aquifer recharge), the total streamflow is derived. This model structure is applied separately to sub-basins showing different hydrology and land use. The model is calibrated at Mojo cross-section, where daily streamflow data are available. Point rainfall and temperature data are spatially averaged with respect to the considered sub-basins. Model calibration and validation are carried out for the period 1984–1986 and 1987–1988 respectively.

scholarly journals Technical Note: Updating procedure for flood forecasting with conceptual HBV-type models

2006 ◽  
Vol 10 (6) ◽  
pp. 783-788 ◽  
Author(s):  
Th. Wöhling ◽  
F. Lennartz ◽  
M. Zappa
Keyword(s):  
Flood Forecasting ◽  
Technical Note ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Mountainous Catchments ◽  
Rainfall Runoff Model ◽  
Updating Procedure ◽  
Global And Local ◽  
Hbv Model ◽  
Runoff Model

Abstract. Flood forecasting is of increasing importance as it comes to an increasing variability in global and local climates. But rainfall-runoff models are far from being perfect. In order to achieve a better prediction for emerging flood events, the model outputs have to be continuously updated. This contribution introduces a rather simple, yet effective updating procedure for the conceptual semi-distributed rainfall-runoff model PREVAH, whose runoff generation module relies on similar algorithms as the HBV-Model. The current conditions of the system, i.e. the contents of the upper soil reservoirs, are updated by the proposed method. The testing of the updating procedure on data from two mountainous catchments in Switzerland reveals a significant increase in prediction accuracy with regards to peak flow.

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