Spatial Delimitation of Small Headwater Catchments and Their Classification in Terms of Runoff Risks

The hydrological similarity of catchments forms a basis for generalizing their hydrological response. This similarity of the hydrological response enables catchments to be classified from numerous perspectives, e.g., hydrological extremes or ecological aspects of catchments. A specific group is formed by so-called “first-order catchments”. This article describes the derivation process of small headwater catchments up to 5 km2 in size on the territory of the Czech Republic. The delimitation is based on the digital terrain model, the stream network, and the water reservoirs. The catchments derived in this way cover 80% of the country. Five mutually independent and sufficiently representative parameters were selected with Principal Components Analysis (PCA), and were used for the cluster analysis performed on two to eight clusters. Clustering Validity Indices (CVI) was used to determine the optimal number of clusters. Subsequently, each generated cluster was assessed for the potential risk of the occurrence of direct runoff, in five classes, on a scale from a moderate degree of risk to a high degree of risk. Six clusters were generated, which is the optimal number in terms of the CVI and their hydrological properties. In this case, 17% of the Czech Republic territory is assessed as lying within a high-risk area, 39% as lying within a medium-risk area, and 24% as lying within a below-average risk area in terms of the occurrence of direct runoff.

Identification of the Relationship between Rainfall and the CN Parameter in Western Carpathian Mountain Catchments in Poland

The aim of this study was to identify the form of the dependence describing the relationship between rainfall (P) and the curve number (CN) parameter using the Natural Resources Conservation Service (NRCS-CN) method in the mountain catchments of the Western Carpathians. The study was carried out in 28 catchments areas in the Western Carpathians in the Upper Vistula Basin, Poland. The study was conducted in the following stages: determination of the volume of the direct runoff using the NRCS-CN method, determination of the P–CN relationship using asymptotic functions, kinetic equation and complementary error function; determination of the volume of the direct runoff from the catchment area, accounting for the correction of the decline; determination of the value of the efficiency coefficient of the analysed models. On the basis of the conducted study, a strong relationship was found between the direct runoff and the rainfall that caused it. The study showed that the empirical values of the CN parameter differed from the values determined on the basis of the volume of rainfall and runoff. The vast majority of study catchments were characterised by a standard P–CN relationship. The kinetic model was found to be the best model to describe the P–CN relationship. The asymptotic model showed the greatest stability for high rainfall episodes. It was shown that the application of the catchment slope correction improved the quality of the NRCS-CN model.

Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments

The SCS-CN method is a globally known procedure used primarily for direct-runoff estimates. It also is integrated in many modelling applications. However, the method was developed in specific geographical conditions, often making its universal applicability problematic. This study aims to determine appropriate values of initial abstraction coefficients λ and curve numbers (CNs), based on measured data in five experimental catchments in the Czech Republic, well representing the physiographic conditions in Central Europe, to improve direct-runoff estimates. Captured rainfall-runoff events were split into calibration and validation datasets. The calibration dataset was analysed by applying three approaches: (1) Modifying λ, both discrete and interpolated, using the tabulated CN values; (2) event analysis based on accumulated rainfall depth at the moment runoff starts to form; and (3) model fitting, an iterative procedure, to search for a pair of λ, S (CN, respectively). To assess individual rainfall characteristics’ possible influence, a principal component analysis and cluster analysis were conducted. The results indicate that the CN method in its traditional arrangement is not very applicable in the five experimental catchments and demands corresponding modifications to determine λ and CN (or S, respectively). Both λ and CN should be viewed as flexible, catchment-dependent (regional) parameters, rather than fixed values. The acquired findings show the need for a systematic yet site-specific revision of the traditional CN method, which may help to improve the accuracy of CN-based rainfall-runoff modelling.

A New Algorithm For The Grid Cell-Based Runoff Routing Model Based on Travel Time Concept

The grid cell-based routing model has recently been used to simulate direct runoff hydrographs at catchment scales. This study develops a flexible event-based runoff routing algorithm to simulate a direct runoff hydrograph (DRH). The experiment was based on the spatiotemporal inputs of a hydrological data set. The flexibility is based on the time step and grid cell size applied in the original STORE-DHM. Rainfall distribution was obtained using radar data adjusted by the measured point ground, while the runoff yield was determined using the NRCS-CN method. The parameter distribution was captured in the GIS environment as raster data formats. Furthermore, it was converted into ASCII data formats for scripting the routing algorithm using Matlab programming codes. The model algorithm was tested for storm events within two small study river systems in Yogyakarta, Indonesia. One event in each catchment was selected and calibrated to the observed hydrograph, treating the Curve Number (CN) and Manning coefficient (n) values as parameter calibrations. In the end, two events were selected for validation. The proposed routing model algorithm simulates DRHs of all selected events in the study areas with excellent performance. The Nash-Sutcliffe coefficient was greater than 0.75 for all DRH during validation, and the volume bias and peak discharge error were less than 25%. Keywords: Algorithm; Cell-based runoff routing; Travel time; GIS; Direct runoff hydrograph. Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Using SCS-CN and Earth Observation for the Comparative Assessment of the Hydrological Effect of Gradual and Abrupt Spatiotemporal Land Cover Changes

In this study a comparative assessment of the impacts of urbanization and of forest fires as well as their combined effect on runoff response is investigated using earth observation and the Soil Conservation Service Curve Number (SCS-CN) direct runoff estimation method in a Mediterranean peri-urban watershed in Attica, Greece. The study area underwent a significant population increase and a rapid increase of urban land uses, especially from the 1980s to the early 2000s. The urbanization process in the studied watershed caused a considerable increase of direct runoff response. A key observation of this study is that the impact of forest fires is much more prominent in rural watersheds than in urbanized watersheds. However, the increments of runoff response are important during the postfire conditions in all cases. Generally, runoff increments due to urbanization seem to be higher than runoff increments due to forest fires affecting the associated hydrological risks. It should also be considered that the effect of urbanization is lasting, and therefore, the possibility of an intense storm to take place is higher than in the case of forest fires that have an abrupt but temporal impact on runoff response. It should be noted though that the combined effect of urbanization and forest fires results in even higher runoff responses. The SCS-CN method, proved to be a valuable tool in this study, allowing the determination of the direct runoff response for each soil, land cover and land management complex in a simple but efficient way. The analysis of the evolution of the urbanization process and the runoff response in the studied watershed may provide a better insight for the design and implementation of flood risk management plans.

Satellite Data Application to Cover Lack of In-situ Observations for Mapping Precipitation and Direct Runoff in Semi-arid Basin

<div> <p>Hydrological modeling in arid basins located in developing countries often lacks sufficient hydrological data because, e.g., rain gauges are typically absent at high elevations and inflow to ungauged areas around large closed lakes such as Lake Urmia is difficult to estimate. We tried to improve precipitation and runoff estimation in Lake Urmia, Iran as an arid basin using satellite-based data. We estimated precipitation using interpolation of rain gauge data by kriging, downscaling Tropical Rainfall Measuring Mission (TRMM), and cokriging interpolation of in-situ records with Remote Sensing (RS)-based data. Using RS-based data in estimations gave more precise results, by compensating for lack of data at high elevations. Cokriging interpolation of rain gauges by TRMM and Digitized Elevation Model (DEM) gave 4–9 mm lower Root Mean Square Error (RMSE) in different years compared with kriging. Downscaling TRMM improved its accuracy by 14 mm. Using the most accurate precipitation model, we modeled annual direct runoff with Kennessey and Soil Conservation Service Curve Number (SCS-CN) models. These models use land use, permeability, slope maps and climatic parameter (Ia) to represent the annual climatic condition of modeled basin in sense of wetness or dryness. In runoff modeling, Kennessey gave higher accuracy in annual scale. It was found that classification of years to wet, dry and normal states in Kennessey by default assumptions on Ia is not accurate enough for semi-arid basins so by solving this issue and calibration Kennessey model parameters, we made this model applicable for Urmia Lake basin. Calibrating Kennessey reduced the Normalized RMSE (NRMSE) from 1 in the standard model to 0.44. Direct runoff coefficient map by 1 km spatial resolution was generated by calibrated Kennessey. Validation by the closest gauges to the lake gave a NRMSE of 0.41 which approved the accuracy of modeling.</p> </div>

Assessment of variation of baseflow contribution to stream flow in a hard-rock aquifer

<p>Stream flow is combination of two major portion of flows as direct runoff and baseflow. Study of baseflow and direct runoff is much needed to understand the hydrology of a watershed, including surface and sub-surface water interaction, and to assess the ecological functioning of streams. Tropical countries like India facing major challenges in water management; especially for irrigation and drinking water. In such regions identification of baseflow sources, knowledge of baseflow availability and analysis of their varied contribution to the stream is needful. Baseflow plays a critical role in maintaining streamflow, especially during pre and post monsoon periods.</p><p>Recursive digital filter technique is adopted for the daily stream flow data measured at river gauge stations on Kabini stream of Cauvery basin, to separate baseflow component from stream flow hydrograph. In terms of hydrogeology, since Cauvery basin occupied with hard-rock terrain, it is important to investigate the intra annual variation of groundwater discharge into the stream. In the present study an attempt has been made by considering daily stream flow data at two river gauge observation points, and annual baseflow and baseflow index is calculated through RDF method. The results obtained from RDF method are validated with the help of hydrogeochemical tracers by applying End Member Mixing Analysis (EMMA) to the hydrogeochemical data for the period of 2018-19 hydrological cycle.</p>

Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment

The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless initial abstraction ratio, which is crucial for an accurate direct runoff estimation with the Curve Number. This ratio is most often assumed to be equal to 0.20, which was originally proposed by the method’s developers. In this work, storm events recorded in the years 2009–2017 in two small Polish catchments of different land use types (urban and agroforested) were analyzed for variability in the initial abstraction ratio across events, seasons, and land use type. Our results showed that: (i) estimated initial abstraction ratios varied between storm events and seasons, and were most often lower than the original value of 0.20; (ii) for large events, the initial abstraction ratio in the catchment approaches a constant value after the rainfall depth exceeds a certain threshold value. Thus, when using the Soil Conservation Service-Curve Number (SCS-CN) method, the initial abstraction ratio should be locally verified, and the conditions for the application of the suggested value of 0.20 should be established.