# GIS Applications to Investigate the Linkage between Geomorphological Catchment Characteristics and Response Time: A Case Study in Four Climatological Regions, South Africa

## Abstract

**:**

## 1. Introduction

^{TM}[14] and open-source, e.g., GRASS [15] and QGIS [16] software packages. Jena and Tiwari [17] also highlighted that the use of GIS software will not only improve catchment parameter estimations but will also contribute towards objective and consistent hydrological assessments.

_{C}), lag time (T

_{L}) and/or time to peak (T

_{P}), as primary input. Bondelid et al. [23] and Gericke and Smithers [24] showed that more than 75% of the total error in design flood estimates in ungauged catchments could be ascribed to errors in the estimation of catchment response time parameters.

^{2}as the upper area limit for ‘small’ catchments characterized by more rapid catchment responses as opposed to larger catchments with longer and more attenuated hydrographs. However, it was also acknowledged that the differences between the two catchment scales may be due to differences in the dominating catchment response mechanisms, i.e., overland flow response in small catchments and channel flow response in larger catchments. In addition to catchment area, other geomorphological catchment characteristics such as shape, hydraulic and main river lengths, average catchment and main river slopes, and drainage density are also regarded as important [20,30,31].

^{TM}environment to estimate a selection of geomorphological catchment characteristics which could have a direct influence on catchment response time and runoff generation. Sixty-five ‘medium-to-large’ gauged catchments (>100 km

^{2}), located in four distinctive climatological regions of South Africa, are used in this case study to investigate the linkage between geomorphological catchment characteristics and observed catchment response time by evaluating the individual and combined influences of catchment geomorphology, channel geomorphology and catchment variables on response time and runoff generation.

## 2. Study Area

^{2}and are regarded as ‘gauged’, since Department of Water and Sanitation (DWS) flow-gauging stations are located at the outlet of each catchment.

## 3. Methods

#### 3.1. Estimation of Catchment Characteristics

#### 3.1.1. Catchment Geomorphology

^{TM}was used to prepare a hydrologically corrected and depressionless DEM. In other words, all ‘sinks’, i.e., cells with a lower elevation compared to the surrounding cells, were filled to generate continuous flow direction and flow accumulation rasters for the identification of catchment areas for specified pour points located at the catchment outlet. The hydrologically corrected DEM was subsequently projected and transformed to enable the estimation of geomorphological catchment characteristics, area (A), perimeter (P), hydraulic length (L

_{H}), centroid distance (L

_{C}), and average slope (S).

_{H}), i.e., the distance measured along the longest river from the catchment outlet to the catchment boundary upstream of the fingertip tributary, was estimated using the Longest Flow Path tool in the Hydrology toolset. The Mean Center tool in the Measuring Geographic Distributions toolset contained in the Spatial Statistics Tools toolbox was used to estimate the centroid of each catchment. The centroid distance (L

_{C}), i.e., the distance along the main river between the outlet and the point on the main river closest to the centroid of the catchment, was established by using the Measure tool in ArcMap [7,14].

_{H}and L

_{C}, the catchment shape was also estimated in terms of a shape factor, and circularity and elongation ratios using Equations (1) to (3), respectively [17,28]:

_{S}is the shape factor, R

_{C}is the circularity ratio, R

_{E}is the elongation ratio, A is the catchment area (km

^{2}), L

_{C}is the centroid distance (km), L

_{H}is the hydraulic length (km), and P is the catchment perimeter (km).

^{TM}. In the case of Equation (5), a slope raster was generated from the DEM using the Slope tool available from the Surface toolset contained in the Spatial Analyst Tools toolbox.

_{1,2}is the average catchment slope (%), A is the catchment area (km

^{2}), ΔH is the contour interval (m), M is the total length of all contour lines within the catchment (km), Δz/Δx is the rate of change of the slope surface in an east-west direction from the center cell, C

_{5}(m·m

^{−1}), Δz/Δy is the rate of change of the slope surface in a north-south direction from the center cell, C

_{5}(m·m

^{−1}), C

_{5}is the center cell, C

_{1–4 & 6–9}are the surrounding cells, N is the number of grid points or cells (8), x

_{c}is the east-west cell size, and y

_{c}is the north-south cell size.

#### 3.1.2. Channel Geomorphology

_{CH}) was estimated using the Longest Flow Path tool in the Hydrology toolset, and the longitudinal profiles were obtained from the DEM using the Stack Profile tool in the Functional Surface toolset contained in the 3D Analyst toolbox. The average slope of the main rivers (S

_{CH}) was estimated using the above GIS-based longitudinal profiles and the following methods [41,42]: (i) Equal-area (Equation (6)), (ii) 10-85 (Equation (7)), and (iii) Taylor-Schwarz (Equation (8)).

_{CH}

_{1–3}is the average main river slope (%), A

_{i}is the incremental area between two consecutive contours (m

^{2}), H

_{B}is the elevation at the catchment outlet (m), H

_{i}is the specific contour interval elevation (m), H

_{T}is the maximum elevation at the river fingertip associated with S

_{CH}(m), H

_{0.10L}is the elevation of the main river at length 0.10L

_{CH}(m), H

_{0.85L}is the elevation of the main river at length 0.85L

_{CH}(m), L

_{CH}is the length of the main river (km), L

_{i}is the distance between two consecutive contours (m), and S

_{i}is the slope between two consecutive contours (m·m

^{−1}).

#### 3.1.3. Catchment Variables

^{TM}according to the generalized CN categories (e.g., agriculture, open space, forest, disturbed land, residential, paved, and commercial industry) as proposed by [35]. Thereafter, the generalized CN categories and the taxonomical soil forms with associated hydrological soil group information were combined using the Union geoprocessing tool in ArcMap. Typically, the hydrological soil group classification [35] represents the runoff potential of soils, i.e., ranging from very permeable (Group A; final infiltration = 25 mm·h

^{−1}and permeability rate >7.6 mm·h

^{−1}) to impermeable (Group D; final infiltration = 3 mm·h

^{−1}and permeability rate < 1.3 mm·h

^{−1}).

#### 3.2. Estimation of Observed Catchment Response Time

_{Px}), were obtained from [38] which determined the average catchment T

_{Px}values using only observed streamflow data. The observed time to peak values for individual flood events (T

_{Pxi}) was expressed as either the net duration of a multi-peaked hydrograph and/or estimated using triangular-shaped direct runoff hydrograph approximations [38]. The ‘average’ catchment response time (T

_{Px}) of all the flood events considered in each catchment was estimated using a linear catchment response function, Equation (9) [38]. Equation (9) is used in this study, since in event-based design flood estimation methods, the design flood estimate is based on a single and representative catchment response time parameter, while the catchment is at an ‘average condition’ [38].

_{Px}is the ‘average’ catchment time to peak based on a linear catchment response function (h), Q

_{Dxi}is the volume of direct runoff for individual flood events (m

^{3}), $\overline{{Q}_{Dx}}$ is the mean of Q

_{Dxi}(m

^{3}), Q

_{Pxi}is the observed peak discharge for individual flood events (m

^{3}·s

^{−1}), $\overline{{Q}_{Px}}$ is the mean of Q

_{Pxi}(m

^{3}·s

^{−1}), N is the sample size, and x is a variable proportionality ratio (default x = 1), which depends on the catchment response time parameter under consideration, i.e., T

_{C}≈ T

_{P}≈ 1 and T

_{L}= 0.6T

_{C}with x = 1.667.

_{Px}) values (dependent variables) and 12 individual catchment characteristics (independent variables) as listed in Table A1, Table A2, Table A3 and Table A4 in Appendix A. Linear backward stepwise multiple regression analysis with deletion at a 95% confidence level was used to illustrate the inclusion of these various independent predictor variables as part of a conceptual catchment response time framework.

## 4. Results and Discussion

_{Tx}), direct runoff volume (Q

_{Dx}), peak flow (Q

_{Px}), and average catchment response time (T

_{Px}, Equation (9)), estimated for the 65 catchments, is listed in Table A1, Table A2, Table A3 and Table A4 in Appendix A. The Q

_{Dx}values listed in these tables were estimated by [38] using the methodology as proposed by [44]. The influences of each catchment variable or parameter contained in these tables are highlighted where applicable in the subsequent sections.

#### 4.1. Catchment Geomorphology

_{S}, Equation (1)) and L

_{C}:L

_{H}ratios < 0.5, combined with steeper upper catchment slopes and flatter valleys, were characterized by shorter catchment response times and higher peak flows compared to those from the long, narrow, similar-sized catchments defined by larger F

_{S}factors. The centroid distance (L

_{C}) values listed in Table A1, Table A2, Table A3 and Table A4 in Appendix A not only confirm that L

_{C}is influenced by the size and shape of a catchment, but also that L

_{C}is influenced by the average catchment slope, especially in catchments with heterogeneous upper and lower catchment slope distributions. The average L

_{C}:L

_{H}ratio of 0.48 obtained confirms that the recommended L

_{C}:L

_{H}ratio of between 0.4 and 0.6 times the distance along the main river [7,42] is sufficiently accurate to be used in the various event-based design flood estimation methods. This is also a more definite guideline than the eyeball estimate as proposed by Alexander [6]. However, practitioners must assess each catchment individually using the tools available in ArcGIS

^{TM}, before just using the proposed L

_{C}:L

_{H}ratios. For example, in many of the SWCR catchments (e.g., G1H008, H2H003, H4H006 and H6H003; Table A3) and ESCR catchments (e.g., T3H002, T5H004 and V6H002; Table A4), due to the steeper average catchment slopes (S

_{2}, Equation (5)) between 14 and 37%, combined with heterogeneous catchment slopes, i.e., large differences between the average catchment slope and main river slopes (S

_{2}:S

_{CH}

_{2}ratios > 25), the L

_{C}:L

_{H}ratios were much lower and varied between 0.21 and 0.38. In addition, it could also be argued that the extensive meandering of the main rivers in the SWCR and ESCR catchments also contributed to larger L

_{H}values, hence, the lower L

_{C}:L

_{H}ratios observed.

_{C}ratios = 1. As shown in Table A1, Table A2, Table A3 and Table A4 in Appendix A, the R

_{C}ratios varied between 1.26 and 2.10 at a catchment level in the four regions. In some of the partially ‘circular catchments’ (1 ≤ R

_{C}< 1.5) with a homogeneous slope distribution in the NR and CR, the runoff from various parts in a catchment tend to reach the catchment outlet simultaneously. The catchments in the CR, and to a lesser extent the NR catchments, are also generally flatter with some surface depressions; hence, the longer catchment response times and lower peaks.

_{C}ratios between 1 and 1.5. In elliptical catchments defined by R

_{C}ratios > 1.5 and elongation ratios (R

_{E}, Equation (3)) less than 0.45, the runoff proved to be more distributed over time, thus resulting in longer catchment response times. Examples thereof, as extracted from Table A1, Table A2, Table A3 and Table A4 in Appendix A, are listed in Table 2.

^{2}value of 0.99 confirms the high degree of association between the results estimated using Equations (4) and (5). The Empirical method’s (Equation (4)) relatively low positive y-intercept value (0.41) and a slope value (1.18) that is larger than unity highlight that this method, despite being based on GIS-based input, has an overall tendency to overestimate the average catchment slope. On average, Equation (4) overestimated the average catchment slope with 18% in all the catchments under consideration when compared to Equation (5). In contrast, Gericke and Du Plessis [7] demonstrated that Equation (4) tends to underestimate the average catchment slopes with between 9 and 43% when compared to Equation (5) applied to the 90-m SRTM DEM data set. However, the latter results were only based on six mutually considered catchments, namely, C5H003, C5H012, 15, 16, 18 and C5H054, located in the Central Region. Differences of up to 46% are evident when the results based on the two versions of Equation (5), i.e., the 30-m (this study) versus 90-m [7] resolutions, are compared, while the two versions of Equation (4) only differ by up to 6%. The latter lower difference of only 6% could be ascribed to the fact that the 90-m and 30-m DEMs are well aligned in terms of horizontal offset; hence, resulting in a comparable catchment area (A) and length, e.g., contour length (M) computations. Hence, in considering the individual M:A ratios (expressed in km·km

^{−2}), it is evident that there is a direct relationship between the M:A ratios and average catchment slopes steeper than 3%, since steeper slopes will result in a higher contour density and associated M values. In considering the reclassified slope raster classes, it was evident that the prediction accuracy of the Empirical method increases with higher M:A ratios, i.e., the average percentage differences between Equations (4) and (5) are less significant. For example, 30% difference (slope class 0–3%), 23% difference (slope class 3–10%), 22% difference (slope class 10–30%), and 19% difference for average catchment slopes > 30%.

#### 4.2. Channel Geomorphology

^{2}values) varying between 0.85 and 0.97. In South Africa, preference is given to the 10-85 method [41], since practitioners regard the Equal-area method largely as a graphical procedure, while the Taylor-Schwarz method is not widely used in South Africa [7]. However, the DWS locally [42] and the National Environmental Research Council internationally [45] recommend the use of the Taylor-Schwarz method (Equation (8)).

_{2}, Equation (5)) and main river slopes (S

_{CH}

_{2}, Equation (7)) is similar in the NR and CR, i.e., the average ratios of the slope descriptors (S

_{2}:S

_{CH}

_{2}) vary between 12 and 15. However, in the SWCR and ESCR, the average S

_{2}:S

_{CH}

_{2}ratios are almost double that, with the average S

_{2}:S

_{CH}

_{2}ratios equal to 27 and 32, respectively.

_{2}:S

_{CH}

_{2}ratios (> 25) and low L

_{C}:L

_{H}ratios (< 0.4), the overall catchment response time proved to be shorter. In other words, runoff volumes reach and concentrate at the catchment centroid much quicker (due to the steeper catchment slope in the upper reaches), and in conjunction with the shorter L

_{C}distances to follow to the catchment outlet, the resulting response time is shorter. Such results are typically evident in catchments H4H006 (S

_{2}:S

_{CH}

_{2}= 63, L

_{C}:L

_{H}= 0.25) and T3H002 (S

_{2}:S

_{CH}

_{2}= 106, L

_{C}:L

_{H}= 0.21).

_{D}), expressed as the ratio of the total length of rivers within a catchment to the catchment area, determines the distance water travels down catchment slopes before reaching the main river reach and is therefore regarded as a key indicator of catchment response time and the resulting runoff due to the differences in velocity and residence time of water between the hill slopes and main rivers. As shown in Table A1, Table A3 and Table A4 in Appendix A, in the well-drained (D

_{D}≈ 0.3) catchments, e.g., A9H002 (NR), H1H018 (SWCR) and U2H006 (ESCR), more rainfall contributed effectively to direct runoff, while the response times were relatively shorter. All the catchments in the NR and CR, with the exception of A2H007 and C5H003, respectively, are characterized by a relatively low drainage density (D

_{D}≤ 0.20), hence, the longer catchment response times and lower peak flows (cf. Table A1 and Table A2).

#### 4.3. Catchment Variables

^{−1}.

#### 4.4. Conceptual Catchment Response Time Framework

^{2}and 2500 km

^{2}≤ A < 6500 km

^{2}) in each climatological region are presented in Figure 5 and Figure 6a,b, respectively.

^{2}; hence, any differences in the catchment response and runoff generation in these catchments are not directly linked to catchment area intrinsically, but are more likely due to the heterogeneity of a combination of other geomorphological catchment characteristics.

_{S}factor (6.95) and lowest R

_{E}ratio (0.42), while catchment A6H006 is regarded as the most fan-shaped catchment with the lowest F

_{S}factor (5.16) and highest R

_{E}ratio (0.60), respectively. Catchments C5H023 and G1H002 are very similar in terms of shape and elongation, while the circularity ratios (R

_{C}) of all four catchments are similar and range between 1.3 and 1.4. Thus, based on shape alone, the catchment response time is expected to be the highest in catchment U2H011, followed by catchments C5H023, G1H002 and A6H006. However, this is not the case and it is clearly evident that the influence of shape on catchment response time in these catchments is overruled by the average catchment and river slopes. Typically, the much steeper average catchment and river slopes in catchments U2H011 (S

_{2}= 14.6% and S

_{CH}

_{2}= 1.3%) and G1H002 (S

_{2}= 33.5% and S

_{CH}

_{2}= 4.5%), resulted in shorter catchment response times, i.e., T

_{Pxi}= 8.4 h and 6.0 h, respectively, as shown in Figure 5, while the peak flows (Q

_{Pxi}) are about five-fold higher than in catchments A6H006 and C5H023.

^{2}as the upper area limit for ‘small’ catchments and claimed that the more rapid catchment response times are due to overland flow conditions being dominant. However, based on the results shown in Figure 5 and the discussion above, it is obvious that catchment response time could not be limited and specifically assigned to pre-defined catchment area ranges (A ≤ 300 km

^{2}) and specific flow regimes without considering the combined influence of different geomorphological catchment characteristics on response time and runoff generation. Hydrological literature (e.g., [46,47,48]) also highlighted that overland flow conditions are limited to the upper reaches of a catchment and depends on the slope and surface roughness.

_{S}factors, low R

_{E}ratios and/or flatter slope (S

_{2}and S

_{CH}

_{2}) values resulting in longer catchment response times, larger direct runoff volumes and lower peaks, was not that prominent in the ‘medium to large’ catchments. However, the lower drainage densities (D

_{D}≤ 0.20) and differences in catchment size (e.g., A2H019 = 6120 km

^{2}; C5H015 = 5939 km

^{2}; H4H006 = 2878 km

^{2}and T3H005 = 2565 km

^{2}) are more significant than the combined influence of the afore-mentioned catchment characteristics.

_{Pxi}< 25 h), lower direct runoff volumes (Q

_{Dxi}≤ 30 × 10

^{6}m

^{3}) and well-defined peaks (Q

_{Pxi}≤ 215 m

^{3}·s

^{−1}) associated with much larger catchment areas (A > 5900 km

^{2}) in the case of catchments A2H019 and C5H015 (Figure 6b) as opposed to the much larger direct runoff volumes (Q

_{Dxi}≈ 74 × 10

^{6}m

^{3}) and peak flows (Q

_{Pxi}> 350 m

^{3}·s

^{−1}) associated with smaller catchment areas less than 2900 km

^{2}in the case of catchments H4H006 and T3H005 (cf. Figure 6a).

_{Px}values; Equation (9)), least square regression analyses in a power form (y = ax

^{b}) yielded the highest r

^{2}values in all cases when the various independent predictor variables, i.e., geomorphological catchment characteristics, were included as part of a conceptual catchment response time framework. Only the six geomorphological catchment characteristics demonstrating a moderate degree of association (r

^{2}value ≥ 0.4) with the observed T

_{Px}values are included in Table 3. A correlation matrix is used to highlight the various relationships.

_{H}is the single best independent predictor variable of T

_{Px}in all the catchments, with r

^{2}= 0.54. However, all the other independent predictor variables could be regarded as equally important, hence, confirming that distinct relationships are not always apparent when individual geomorphological catchment characteristics are considered in isolation to represent the complexities of catchment response time.

_{Py}is the estimated time to peak (h), A is the catchment area (km

^{2}), L

_{C}is the centroid distance (km), L

_{H}is the hydraulic length (km), P is the catchment perimeter (km), S

_{2}is the average catchment slope (Equation (5), %), and S

_{CH}

_{2}is the average river slope (Equation (7), %).

_{Py}(Equation (10)) with the observed T

_{Px}(Equation (9)) values, an improved coefficient of multiple-correlation (R

_{i}

^{2}) = 0.62 and standard error (S

_{Ey}) = 11.9 h were obtained. However, the S

_{Ey}results must be clearly understood in the context of the actual response time associated with catchment area, as the impact of such error in the T

_{Py}estimates might be critical in a small catchment, while being less significant in a larger catchment.

_{Pxi}and estimated T

_{Py}(Equation (10)) values relative to the average observed catchment T

_{Px}values (Equation (9)) in each catchment is estimated using Equation (11). The latter catchment response time variability at a catchment level in the four climatological regions are shown in Figure 8.

_{P}is the catchment response time variability (positive = overestimation and negative = underestimation), T

_{Px}is the average observed catchment response time (Equation (9), h), T

_{Pxi}is the individual-event observed catchment response time expressed as the net duration of a multi-peaked hydrograph (h), and T

_{Py}is the estimated catchment response time (Equation (10), h).

_{Pxi}variability, as depicted in Figure 8 and expressed using Equation (11), highlights that the variability in observed catchment response times is not solely related to catchment area, but the increase in variability is most likely associated with an increase in the spatial and temporal distribution and heterogeneity of other geomorphological catchment characteristics and rainfall as the catchment scale increases. Typically, at these catchment scales, the largest Q

_{Pxi}and T

_{Pxi}values are associated with the likelihood of the entire catchment receiving rainfall for the critical storm duration. Smaller T

_{Pxi}values could be expected when effective rainfall of high average intensity does not cover the entire catchment, especially when a rainfall event is centered near the catchment outlet. However, these smaller T

_{Pxi}values are likely to occur more frequently; hence, having a larger influence on the average value and consequently might result in an underestimated representative catchment T

_{Px}value. On the other hand, the longer T

_{Pxi}values have a lower frequency of occurrence and are reasonable at medium to large catchment scales as the contribution of the whole catchment to peak discharge seldom occurs as a result of the non-uniform spatial and temporal distribution of rainfall. Ultimately, it can be concluded that catchment response time variability increases as the magnitude (e.g., AEP) and spatial distribution of rainfall events decrease.

_{Py}estimates are well within the bounds of the high individual-event observed T

_{Pxi}variability in each catchment. However, since the purpose of this study is not to derive an empirical catchment response time equation, the further refinement of Equation (10) in terms of calibration, verification and possible regionalization is acknowledged. Equation (10) was purposely derived to illustrate that the response of a catchment is most likely to be influenced by a combination of geomorphological catchment characteristics and not by a single catchment characteristic. Furthermore, as in agreement with the findings of [25], the inclusion of slope predictors (S

_{2}and S

_{CH}

_{2}) is regarded as essential to ensure that both the size (A) and distance (L

_{C}and L

_{H}) predictors provide a good indication of catchment response times. The distance predictors, in conjunction with the catchment perimeter (P), also proved to be useful in describing the catchment shape when used in combination with the catchment area.

## 5. Conclusions

- A more diverse selection of catchment parameters could be considered as opposed to when manual methods are used and were included as independent predictor variables in the conceptual catchment response time framework to evaluate the individual and combined influences of catchment geomorphology, channel geomorphology and catchment variables on response time and runoff generation.
- The inherent human and instrumentation errors associated with manual data acquisition processes are eliminated. However, the original meta data used in any GIS-based approach must always be obtained from reputable data custodians and/or repositories.
- The time and effort to extract information manually not only limit the number of catchment parameters being considered by researchers when undertaking multiple regression analysis and regionalization procedures, but also lead to systematic errors and inconsistent methodologies, which are not necessarily well documented and/or recognized by the broader scientific community. In using a GIS-based approach, a trade-off between time and accuracy could be used to provide results at a pre-defined or required resolution and accuracy.

^{2}≤ 0.97) between the various methods (Equations (6)–(8)) used to estimate the average main river slopes confirmed that any of these methods could be used with confidence. However, preference is given to the 10-85 method (Equation (7)), since it is more user friendly to use than the other two methods, while being equally accurate.

^{TM}was successfully applied, but that any of these methods could also be used satisfactorily and with confidence in flood hydrology. Such improved estimations of geomorphological catchment characteristics are not only essential to both regionalization procedures and the actual estimation of design floods, but it will also impact on the successful deployment thereof. Hence, taking into consideration the significant influence catchment response times have on the resulting hydrograph shape and peak flow, it is obvious that the accuracy of these GIS-based catchment parameter estimation methods, irrespective of the software package used, will also have an indirect impact on the design of hydraulic structures.

_{S}), L

_{C}:L

_{H}ratios (<0.5) and circularity ratios (1 ≤ R

_{C}< 1.5), and associated higher elongation ratios (R

_{E}> 0.5), S:S

_{CH}ratios (>25) and drainage densities (D

_{D}≈ 0.3).

^{2}, the response time was primarily influenced and governed by the average catchment and river slopes, i.e., the S:S

_{CH}ratios. In catchment areas between 2500 and 6500 km

^{2}, no distinctive linkage was apparent between the observed catchment response time and catchment shape, average catchment and river slopes. At these catchment scales, the combined influence of the latter catchment parameters was less significant than the differences in catchment size and drainage densities. The type, spatial and temporal distribution of rainfall were identified as possible candidates that govern the overall catchment response time at medium to large catchment scales, but the quantitative investigation thereof is beyond the scope of this study and could therefore not be confirmed. However, it was also evident that catchment response time could not be limited and specifically assigned to pre-defined catchment area ranges and associated flow regimes without considering the combined influence of the above-mentioned geomorphological catchment characteristics and rainfall characteristics. In other words, the variability in observed catchment response times is not exclusively related to catchment area, but rather associated with the increasing spatial–temporal heterogeneity of other geomorphological catchment characteristics and rainfall as the catchment scale increases.

## Funding

## Acknowledgments

## Conflicts of Interest

## Appendix A

**Table A1.**Geomorphological catchment characteristics, average hydrograph and catchment response time information in the Northern Region (after [25]).

Catchment | A2H005 | A2H006 | A2H007 | A2H012 | A2H013 | A2H015 | A2H017 | A2H019 |

A (km^{2}) | 774 | 1030 | 145 | 2555 | 1161 | 23,852 | 1082 | 6120 |

P (km) | 136 | 177 | 64 | 260 | 179 | 808 | 180 | 415 |

L_{H} (km) | 51 | 86 | 17 | 57 | 64 | 252 | 76 | 132 |

L_{C} (km) | 27 | 51 | 7 | 22 | 37 | 130 | 40 | 73 |

F_{S} (Equation (1)) | 8.74 | 12.40 | 4.25 | 8.53 | 10.32 | 22.60 | 11.14 | 15.67 |

R_{C} (Equation (2)) | 1.38 | 1.55 | 1.50 | 1.45 | 1.48 | 1.48 | 1.55 | 1.50 |

R_{E} (Equation (3)) | 0.62 | 0.42 | 0.79 | 0.99 | 0.60 | 0.69 | 0.49 | 0.67 |

Σ Contours M (km) | 1354 | 2979 | 548 | 8247 | 4951 | 73,110 | 4842 | 21,701 |

S_{1} (Equation (4), %) | 3.50 | 5.78 | 7.57 | 6.46 | 8.53 | 6.13 | 8.95 | 7.09 |

S_{2} (Equation (5), %) | 2.73 | 4.76 | 6.52 | 5.30 | 7.03 | 5.13 | 7.43 | 5.78 |

L_{CH} (km) | 48 | 86 | 17 | 57 | 57 | 251 | 76 | 132 |

S_{CH}_{1} (Equation (6), %) | 0.41 | 0.37 | 1.27 | 0.56 | 0.42 | 0.13 | 0.42 | 0.29 |

S_{CH}_{2} (Equation (7), %) | 0.44 | 0.39 | 1.47 | 0.69 | 0.52 | 0.19 | 0.49 | 0.36 |

S_{CH}_{3} (Equation (8), %) | 0.45 | 0.35 | 1.33 | 0.54 | 0.46 | 0.11 | 0.45 | 0.24 |

D_{D} (km·km^{−2}) | 0.09 | 0.17 | 0.24 | 0.14 | 0.12 | 0.13 | 0.12 | 0.14 |

Dolomitic areas (%) | 61.2 | 12.4 | 30.6 | 44.2 | 13.9 | 12.5 | 0.0 | 21.1 |

Weighted CN value | 74.8 | 72.4 | 77.3 | 69.8 | 71.6 | 69.3 | 71.2 | 69.6 |

No. of flood events | 60 | 100 | 60 | 70 | 60 | 15 | 18 | 60 |

Q_{Tx} (10^{6} m^{3}) | 2.1 | 8.6 | 0.8 | 17.3 | 6 | 12.6 | 1.4 | 42.3 |

Q_{Dx} (10^{6} m^{3}) | 1.7 | 6.4 | 0.7 | 11 | 3.9 | 10.7 | 1.2 | 33.5 |

Q_{Px} (m^{3}·s^{−1}) | 14.7 | 79.8 | 40.2 | 190.9 | 80.3 | 85.8 | 29.6 | 205.1 |

T_{Px} (Equation (9), h) | 14.3 | 11.2 | 4.1 | 12.4 | 8 | 28.8 | 6.2 | 25.5 |

Catchment | A2H020 | A2H021 | A3H001 | A5H004 | A6H006 | A7H003 | A9H001 | A9H002 |

A (km^{2}) | 4546 | 7483 | 1175 | 636 | 180 | 6700 | 914 | 103 |

P (km) | 347 | 459 | 174 | 140 | 63 | 396 | 186 | 76 |

L_{H} (km) | 176 | 216 | 47 | 68 | 25 | 162 | 82 | 38 |

L_{C} (km) | 61 | 70 | 17 | 37 | 9 | 79 | 44 | 19 |

F_{S} (Equation (1)) | 16.22 | 17.92 | 7.45 | 10.53 | 5.16 | 17.08 | 11.70 | 7.19 |

R_{C} (Equation (2)) | 1.45 | 1.50 | 1.44 | 1.57 | 1.32 | 1.37 | 1.73 | 2.10 |

R_{E} (Equation (3)) | 0.43 | 0.45 | 0.82 | 0.42 | 0.60 | 0.57 | 0.42 | 0.30 |

Σ Contours M (km) | 14,174 | 13,131 | 2270 | 3102 | 665 | 11,629 | 6332 | 1114 |

S_{1} (Equation (4), %) | 6.24 | 3.51 | 3.87 | 9.75 | 7.40 | 3.47 | 13.86 | 21.59 |

S_{2} (Equation (5), %) | 5.31 | 2.85 | 3.13 | 8.73 | 6.32 | 2.71 | 10.17 | 17.47 |

L_{CH} (km) | 176 | 215 | 47 | 68 | 25 | 162 | 82 | 38 |

S_{CH}_{1} (Equation (6), %) | 0.22 | 0.14 | 0.68 | 0.58 | 0.92 | 0.32 | 0.43 | 1.37 |

S_{CH}_{2} (Equation (7), %) | 0.34 | 0.19 | 0.73 | 0.71 | 1.10 | 0.33 | 0.50 | 2.01 |

S_{CH}_{3} (Equation (8), %) | 0.20 | 0.13 | 0.72 | 0.59 | 0.92 | 0.34 | 0.34 | 0.89 |

D_{D} (km·km^{−2}) | 0.14 | 0.13 | 0.13 | 0.19 | 0.14 | 0.09 | 0.16 | 0.37 |

Dolomitic areas (%) | 0.1 | 7.9 | 79.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 70.7 | 69.7 | 68.9 | 63.6 | 61.1 | 61.5 | 68.4 | 68.5 |

No. of flood events | 40 | 30 | 50 | 30 | 65 | 40 | 60 | 16 |

Q_{Tx} (10^{6} m^{3}) | 28.3 | 74.8 | 1 | 19.5 | 1.9 | 7.1 | 15.8 | 6.5 |

Q_{Dx} (10^{6} m^{3}) | 22.8 | 49 | 0.8 | 10.3 | 1.5 | 5.8 | 10.8 | 3.9 |

Q_{Px} (m^{3}·s^{−1}) | 250 | 145.3 | 34 | 89.6 | 21.5 | 53.6 | 58.8 | 66.7 |

T_{Px} (Equation (9), h) | 24.4 | 79.6 | 3.3 | 19 | 12.4 | 19.9 | 30.2 | 7.5 |

**Table A2.**Geomorphological catchment characteristics, average hydrograph and catchment response time information in the Central Region (after [25]).

Catchment | C5H003 | C5H006 | C5H007 | C5H008 | C5H009 | C5H012 | C5H014 | C5H015 |

A (km^{2}) | 1641 | 676 | 346 | 598 | 189 | 2366 | 31,283 | 5939 |

P (km) | 196 | 145 | 100 | 122 | 71 | 230 | 927 | 384 |

L_{H} (km) | 71 | 64 | 41 | 41 | 24 | 87 | 326 | 160 |

L_{C} (km) | 41 | 29 | 17 | 22 | 14 | 45 | 207 | 81 |

F_{S} (Equation (1)) | 10.95 | 9.61 | 7.17 | 7.74 | 5.73 | 11.98 | 28.12 | 17.15 |

R_{C} (Equation (2)) | 1.36 | 1.58 | 1.52 | 1.40 | 1.45 | 1.34 | 1.48 | 1.41 |

R_{E} (Equation (3)) | 0.64 | 0.46 | 0.51 | 0.67 | 0.64 | 0.63 | 0.61 | 0.54 |

Σ Contours M (km) | 4009 | 901 | 386 | 1732 | 419 | 4757 | 42,538 | 10,575 |

S_{1} (Equation (4), %) | 4.89 | 2.67 | 2.23 | 5.80 | 4.44 | 4.02 | 2.72 | 3.56 |

S_{2} (Equation (5), %) | 3.90 | 2.02 | 1.75 | 4.83 | 3.66 | 3.28 | 2.13 | 2.77 |

L_{CH} (km) | 71 | 64 | 40 | 41 | 24 | 87 | 326 | 160 |

S_{CH}_{1} (Equation (6), %) | 0.23 | 0.24 | 0.30 | 0.41 | 0.55 | 0.21 | 0.10 | 0.11 |

S_{CH}_{2} (Equation (7), %) | 0.26 | 0.27 | 0.34 | 0.48 | 0.60 | 0.27 | 0.10 | 0.14 |

S_{CH}_{3} (Equation (8), %) | 0.24 | 0.28 | 0.34 | 0.46 | 0.62 | 0.23 | 0.09 | 0.11 |

D_{D} (km·km^{−2}) | 0.23 | 0.18 | 0.19 | 0.17 | 0.19 | 0.18 | 0.11 | 0.20 |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 68.0 | 73.6 | 73.4 | 67.3 | 67.1 | 67.3 | 68.8 | 69.8 |

No. of flood events | 101 | 14 | 91 | 112 | 13 | 68 | 28 | 90 |

Q_{Tx} (10^{6} m^{3}) | 2.1 | 1.4 | 1.2 | 2.2 | 1 | 3.3 | 46.7 | 23.3 |

Q_{Dx} (10^{6} m^{3}) | 1.7 | 1.3 | 1 | 2 | 0.8 | 2.3 | 36.5 | 21 |

Q_{Px} (m^{3}·s^{−1}) | 32.8 | 36 | 28 | 44.7 | 14.3 | 41.5 | 168.3 | 203.1 |

T_{Px} (Equation (9), h) | 11.1 | 8.2 | 7.2 | 10.5 | 12.7 | 11.9 | 56.6 | 25 |

Catchment | C5H016 | C5H018 | C5H023 | C5H035 | C5H039 | C5H053 | C5H054 | |

A (km^{2}) | 33,278 | 17,361 | 185 | 17,359 | 6331 | 4569 | 687 | |

P (km) | 980 | 730 | 65 | 730 | 411 | 329 | 146 | |

L_{H} (km) | 378 | 375 | 29 | 373 | 187 | 120 | 68 | |

L_{C} (km) | 230 | 174 | 17 | 173 | 103 | 56 | 33 | |

F_{S} (Equation (1)) | 30.33 | 27.83 | 6.48 | 27.72 | 19.28 | 14.05 | 10.07 | |

R_{C} (Equation (2)) | 1.52 | 1.56 | 1.35 | 1.56 | 1.46 | 1.37 | 1.57 | |

R_{E} (Equation (3)) | 0.54 | 0.40 | 0.52 | 0.40 | 0.48 | 0.64 | 0.44 | |

Σ Contours M (km) | 44,532 | 19,437 | 764 | 19,437 | 10,766 | 9064 | 933 | |

S_{1} (Equation (4), %) | 2.68 | 2.24 | 8.28 | 2.24 | 3.40 | 3.97 | 2.72 | |

S_{2} (Equation (5), %) | 2.09 | 1.72 | 7.09 | 1.72 | 2.65 | 3.08 | 2.07 | |

L_{CH} (km) | 378 | 375 | 29 | 373 | 187 | 119 | 67 | |

S_{CH}_{1} (Equation (6), %) | 0.11 | 0.08 | 0.52 | 0.08 | 0.09 | 0.15 | 0.25 | |

S_{CH}_{2} (Equation (7), %) | 0.10 | 0.08 | 0.58 | 0.08 | 0.13 | 0.18 | 0.26 | |

S_{CH}_{3} (Equation (8), %) | 0.09 | 0.08 | 0.60 | 0.08 | 0.10 | 0.16 | 0.28 | |

D_{D} (km·km^{−2}) | 0.10 | 0.09 | 0.20 | 0.09 | 0.20 | 0.21 | 0.18 | |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |

Weighted CN value | 69.0 | 70.1 | 67.9 | 70.1 | 69.8 | 69.8 | 73.6 | |

No. of flood events | 40 | 50 | 58 | 20 | 56 | 65 | 60 | |

Q_{Tx} (10^{6} m^{3}) | 31 | 22.8 | 0.8 | 10.8 | 34 | 8.3 | 1.3 | |

Q_{Dx} (10^{6} m^{3}) | 27 | 19.7 | 0.6 | 9.1 | 29.2 | 5.7 | 0.8 | |

Q_{Px} (m^{3}·s^{−1}) | 105.6 | 105 | 15.6 | 58.9 | 136.2 | 93.1 | 21.3 | |

T_{Px} (Equation (9), h) | 65.6 | 39 | 9.8 | 40.7 | 55.7 | 16.4 | 8.7 |

**Table A3.**Geomorphological catchment characteristics, average hydrograph and catchment response time information in the Southern Winter Coastal Region (after [25]).

Catchment | G1H002 | G1H007 | G1H008 | G4H005 | H1H003 | H1H006 |

A (km^{2}) | 186 | 724 | 394 | 146 | 656 | 753 |

P (km) | 65 | 128 | 93 | 60 | 130 | 135 |

L_{H} (km) | 28 | 56 | 26 | 30 | 39 | 47 |

L_{C} (km) | 13 | 29 | 6 | 14 | 22 | 30 |

F_{S} (Equation (1)) | 5.91 | 9.16 | 4.49 | 6.15 | 7.62 | 8.80 |

R_{C} (Equation (2)) | 1.34 | 1.35 | 1.32 | 1.41 | 1.43 | 1.38 |

R_{E} (Equation (3)) | 0.55 | 0.55 | 0.87 | 0.46 | 0.74 | 0.66 |

Σ Contours M (km) | 3781 | 11,768 | 4446 | 1789 | 6969 | 9968 |

S_{1} (Equation (4), %) | 40.74 | 32.52 | 22.58 | 24.55 | 21.26 | 26.49 |

S_{2} (Equation (5), %) | 33.53 | 26.21 | 18.89 | 20.71 | 16.41 | 21.20 |

L_{CH} (km) | 28 | 55 | 26 | 29 | 38 | 46 |

S_{CH}_{1} (Equation (6), %) | 4.05 | 0.41 | 1.37 | 1.06 | 0.73 | 1.05 |

S_{CH}_{2} (Equation (7), %) | 4.49 | 0.46 | 1.61 | 1.58 | 0.89 | 0.96 |

S_{CH}_{3} (Equation (8), %) | 2.95 | 0.29 | 1.04 | 0.17 | 0.68 | 0.74 |

D_{D} (km·km^{−2}) | 0.22 | 0.21 | 0.21 | 0.20 | 0.17 | 0.18 |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 59.2 | 61.5 | 67.9 | 64.1 | 67.4 | 66.5 |

No. of flood events | 90 | 75 | 75 | 55 | 72 | 90 |

Q_{Tx} (10^{6} m^{3}) | 8.1 | 50.4 | 12.2 | 15.8 | 15.1 | 25.9 |

Q_{Dx} (10^{6} m^{3}) | 5.8 | 43.9 | 8.5 | 12.5 | 11.6 | 18.1 |

Q_{Px} (m^{3}·s^{−1}) | 123.8 | 238.9 | 139.5 | 79.7 | 115 | 273.6 |

T_{Px} (Equation (9), h) | 6.4 | 37.1 | 10.8 | 32.4 | 21.2 | 15.1 |

Catchment | H1H018 | H2H003 | H3H001 | H4H006 | H6H003 | H7H003 |

A (km^{2}) | 109 | 743 | 594 | 2 878 | 500 | 458 |

P (km) | 60 | 154 | 123 | 304 | 135 | 126 |

L_{H} (km) | 23 | 62 | 52 | 110 | 39 | 48 |

L_{C} (km) | 9 | 20 | 23 | 27 | 14 | 23 |

F_{S} (Equation (1)) | 4.98 | 8.44 | 8.42 | 11.00 | 6.55 | 8.22 |

R_{C} (Equation (2)) | 1.61 | 1.60 | 1.43 | 1.60 | 1.71 | 1.67 |

R_{E} (Equation (3)) | 0.52 | 0.50 | 0.53 | 0.55 | 0.65 | 0.50 |

Σ Contours M (km) | 2617 | 15,144 | 8878 | 46,243 | 7974 | 6375 |

S_{1} (Equation (4), %) | 47.85 | 40.77 | 29.88 | 32.13 | 31.92 | 27.85 |

S_{2} (Equation (5), %) | 41.61 | 37.06 | 23.92 | 29.21 | 25.56 | 23.13 |

L_{CH} (km) | 23 | 60 | 52 | 102 | 38 | 47 |

S_{CH}_{1} (Equation (6), %) | 2.91 | 1.15 | 0.51 | 0.35 | 0.54 | 0.94 |

S_{CH}_{2} (Equation (7), %) | 3.20 | 1.54 | 0.56 | 0.47 | 0.97 | 0.94 |

S_{CH}_{3} (Equation (8), %) | 2.11 | 1.08 | 0.40 | 0.26 | 0.14 | 0.67 |

D_{D} (km·km^{−2}) | 0.28 | 0.20 | 0.18 | 0.19 | 0.21 | 0.21 |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 67.1 | 62.4 | 70.5 | 64.2 | 61.7 | 67.4 |

No. of flood events | 80 | 45 | 25 | 80 | 52 | 70 |

Q_{Tx} (10^{6} m^{3}) | 15 | 7.6 | 5.6 | 105.7 | 16.9 | 8.3 |

Q_{Dx} (10^{6} m^{3}) | 11 | 5.3 | 5.2 | 78.8 | 13.1 | 7.3 |

Q_{Px} (m^{3}·s^{−1}) | 323.3 | 67.9 | 97.8 | 453.5 | 58.1 | 74.7 |

T_{Px} (Equation (9), h) | 10.9 | 12.8 | 12.5 | 44.8 | 32.1 | 16.5 |

**Table A4.**Geomorphological catchment characteristics, average hydrograph and catchment response time information in the Eastern Summer Coastal Region (after [25]).

Catchment | T1H004 | T3H002 | T3H004 | T3H005 | T3H006 | T4H001 | T5H001 | T5H004 | U2H005 | U2H006 | U2H011 |

A (km^{2}) | 4923 | 2102 | 1027 | 2565 | 4282 | 723 | 3639 | 537 | 2523 | 338 | 176 |

P (km) | 333 | 226 | 187 | 299 | 356 | 131 | 329 | 123 | 282 | 108 | 65 |

L_{H} (km) | 205 | 109 | 103 | 160 | 197 | 68 | 200 | 67 | 175 | 49 | 36 |

L_{C} (km) | 99 | 23 | 50 | 87 | 113 | 32 | 85 | 24 | 70 | 23 | 18 |

F_{S} (Equation (1)) | 19.59 | 10.42 | 12.98 | 17.49 | 20.14 | 10.01 | 18.59 | 9.16 | 16.83 | 8.22 | 6.95 |

R_{C} (Equation (2)) | 1.34 | 1.39 | 1.64 | 1.66 | 1.53 | 1.37 | 1.54 | 1.50 | 1.59 | 1.66 | 1.39 |

R_{E} (Equation (3)) | 0.39 | 0.47 | 0.35 | 0.36 | 0.37 | 0.45 | 0.34 | 0.39 | 0.32 | 0.42 | 0.42 |

Σ Contours M (km) | 39,639 | 21,877 | 8540 | 32,729 | 42,893 | 7769 | 39,077 | 7605 | 19,572 | 2767 | 1526 |

S_{1} (Equation (4), %) | 16.10 | 20.82 | 16.64 | 25.52 | 20.03 | 21.49 | 21.48 | 28.31 | 15.52 | 16.36 | 17.31 |

S_{2} (Equation (5), %) | 13.39 | 15.01 | 14.46 | 21.42 | 16.76 | 16.59 | 17.75 | 22.66 | 12.71 | 12.77 | 14.60 |

L_{CH} (km) | 205 | 109 | 103 | 160 | 197 | 68 | 199 | 67 | 174 | 49 | 35 |

S_{CH}_{1} (Equation (6), %) | 0.39 | 0.19 | 0.36 | 0.50 | 0.34 | 0.85 | 0.56 | 0.69 | 0.60 | 0.42 | 1.16 |

S_{CH}_{2} (Equation (7), %) | 0.50 | 0.14 | 0.34 | 0.45 | 0.34 | 0.95 | 0.61 | 0.77 | 0.68 | 0.67 | 1.28 |

S_{CH}_{3} (Equation (8), %) | 0.32 | 0.14 | 0.26 | 0.38 | 0.21 | 0.89 | 0.41 | 0.52 | 0.34 | 0.13 | 1.18 |

D_{D} (km·km^{−2}) | 0.20 | 0.19 | 0.20 | 0.25 | 0.24 | 0.25 | 0.21 | 0.18 | 0.24 | 0.30 | 0.20 |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 70.5 | 66.5 | 70.3 | 69.0 | 71.7 | 69.7 | 70.2 | 68.5 | 68.1 | 75.2 | 72.6 |

No. of flood events | 80 | 67 | 38 | 60 | 75 | 30 | 42 | 30 | 36 | 32 | 40 |

Q_{Tx} (10^{6} m^{3}) | 42.9 | 46.2 | 18.5 | 97 | 155.8 | 37.3 | 255.3 | 46.9 | 68.3 | 25.5 | 6.2 |

Q_{Dx} (10^{6} m^{3}) | 30.7 | 26.1 | 10.1 | 53.6 | 92.5 | 18.7 | 187.4 | 28.6 | 39.7 | 17.3 | 3.5 |

Q_{Px} (m^{3}·s^{−1}) | 271.7 | 203.6 | 48.2 | 385.7 | 552 | 184.8 | 444.6 | 117.8 | 151.3 | 50 | 95.6 |

T_{Px} (Equation (9), h) | 30.8 | 28.8 | 37.2 | 34.9 | 39.6 | 24.8 | 57.7 | 25.7 | 32.2 | 35.7 | 8.8 |

Catchment | U2H012 | U2H013 | U4H002 | V1H004 | V1H009 | V2H001 | V2H002 | V3H005 | V3H007 | V5H002 | V6H002 |

A (km^{2}) | 431 | 296 | 317 | 446 | 195 | 1951 | 945 | 677 | 128 | 28,893 | 12,854 |

P (km) | 99 | 91 | 88 | 108 | 62 | 271 | 148 | 134 | 66 | 1098 | 594 |

L_{H} (km) | 57 | 51 | 48 | 42 | 28 | 188 | 105 | 86 | 25 | 505 | 312 |

L_{C} (km) | 25 | 29 | 23 | 23 | 15 | 87 | 48 | 50 | 17 | 287 | 118 |

F_{S} (Equation (1)) | 8.80 | 8.91 | 8.20 | 7.82 | 6.17 | 18.39 | 12.90 | 12.33 | 6.13 | 35.35 | 23.47 |

R_{C} (Equation (2)) | 1.34 | 1.50 | 1.40 | 1.45 | 1.26 | 1.73 | 1.36 | 1.45 | 1.64 | 1.82 | 1.48 |

R_{E} (Equation (3)) | 0.41 | 0.38 | 0.42 | 0.56 | 0.56 | 0.26 | 0.33 | 0.34 | 0.51 | 0.38 | 0.41 |

Σ Contours M (km) | 2870 | 2714 | 2179 | 9239 | 1069 | 14,882 | 7625 | 4379 | 1299 | 234,676 | 109,087 |

S_{1} (Equation (4), %) | 13.33 | 18.35 | 13.74 | 41.39 | 10.96 | 15.26 | 16.15 | 12.94 | 20.22 | 16.24 | 16.97 |

S_{2} (Equation (5), %) | 11.15 | 14.91 | 11.31 | 34.00 | 8.71 | 12.47 | 12.80 | 11.75 | 15.73 | 13.52 | 14.09 |

L_{CH} (km) | 57 | 50 | 48 | 42 | 28 | 188 | 105 | 86 | 25 | 504 | 312 |

S_{CH}_{1} (Equation (6), %) | 0.65 | 1.20 | 0.44 | 1.58 | 0.66 | 0.58 | 0.34 | 0.28 | 0.95 | 0.25 | 0.29 |

S_{CH}_{2} (Equation (7), %) | 0.68 | 1.78 | 0.65 | 2.13 | 0.58 | 0.40 | 0.41 | 0.25 | 0.93 | 0.27 | 0.24 |

S_{CH}_{3} (Equation (8), %) | 0.56 | 0.78 | 0.37 | 1.36 | 0.66 | 0.25 | 0.27 | 0.19 | 0.87 | 0.19 | 0.17 |

D_{D} (km·km^{−2}) | 0.25 | 0.17 | 0.15 | 0.28 | 0.14 | 0.23 | 0.24 | 0.18 | 0.19 | 0.19 | 0.19 |

Dolomitic areas (%) | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |

Weighted CN value | 68.3 | 70.0 | 67.5 | 72.3 | 73.6 | 71.3 | 72.1 | 69.7 | 65.1 | 70.3 | 71.6 |

No. of flood events | 40 | 52 | 30 | 38 | 70 | 62 | 45 | 60 | 58 | 75 | 30 |

Q_{Tx} (10^{6} m^{3}) | 7.6 | 11.9 | 10.3 | 19 | 4.4 | 77.1 | 62.4 | 27.2 | 7 | 635.1 | 704.7 |

Q_{Dx} (10^{6} m^{3}) | 4.4 | 7.1 | 6.7 | 12.6 | 3.8 | 60.8 | 41.6 | 19.5 | 4.7 | 385.8 | 456.5 |

Q_{Px} (m^{3}·s^{−1}) | 72.7 | 58.2 | 19.9 | 119.8 | 150.8 | 191.5 | 136 | 72.6 | 51.1 | 1430.4 | 1136.6 |

T_{Px} (Equation (9), h) | 6.4 | 9.9 | 31.1 | 8.9 | 5.6 | 47.1 | 59.8 | 37.2 | 9.1 | 65.3 | 67.7 |

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**Figure 2.**(

**a**) Digital Elevation Model (DEM) of the Northern Region. The altitude above mean sea level (MSL) varies between 544 and 2089 m. The river network shown is characterized by drainage densities (D

_{D}) at a catchment level ranging between 0.09 and 0.24. (

**b**) DEM of the Central Region. The altitude above MSL varies between 993 and 2130 m. The river network shown is characterized by drainage densities (D

_{D}) at a catchment level ranging between 0.11 and 0.23. (

**c**) DEM of the Southern Winter Coastal Region. The altitude above MSL varies between 0 and 2235 m. The river network shown is characterized by drainage densities (D

_{D}) at a catchment level ranging between 0.17 and 0.28. (

**d**) DEM of the Eastern Summer Coastal Region. The altitude above MSL varies between 0 and 3420 m. The river network shown is characterized by drainage densities (D

_{D}) at a catchment level ranging between 0.14 and 0.30.

**Figure 4.**Scatter plot of the average river slope values estimated using Equations (6)–(8). The degree of association (r

^{2}values) between the different methods range between 0.85 (Equation (7) vs. Equation (8)) and 0.97 (Equation (6) vs. Equation (7)).

**Figure 5.**Examples of observed hydrographs representative of the ‘average conditions’ in ‘small’ catchments (100 km

^{2}≤ A < 200 km

^{2}) in each climatological region.

**Figure 6.**(

**a**) Examples of observed hydrographs representative of the ‘average conditions’ in ‘medium’ catchments (2500 km

^{2}≤ A < 3000 km

^{2}) in the SWCR and ESCR. (

**b**) Examples of observed hydrographs representative of the ‘average conditions’ in ‘large’ catchments (5500 km

^{2}≤ A < 6500 km

^{2}) in the NR and CR.

**Figure 7.**Relationship between the average catchment response time (Equation (9)) as the criterion variable and the hydraulic length (L

_{H}) as the predictor variable in the 65 catchments.

**Figure 8.**Catchment response time variability (Equation (11)) at a catchment level in the four climatological regions.

**Table 1.**Main properties of the 65 catchments located in the four climatological regions (after [38]).

Range Descriptors | Climatological Regions | |||
---|---|---|---|---|

NR | CR | SWCR | ESCR | |

Secondary drainage regions | A2, A3, A5–A7 and A9 | C5 | G1, G4, H1–H4, H6 and H7 | T1, T3–T5, U2, U4, V1–V3 and V5–V6 |

Number of catchments | 16 | 15 | 12 | 22 |

Catchment area (km^{2}) | 103–23,852 | 185–33,278 | 109–2878 | 129–28,893 |

Altitude above MSL (m) | 544–1763 | 1021–2120 | 86–2060 | 31–3149 |

Average catchment slope (%) | 3–18 | 2–7 | 16–42 | 11–34 |

MAP (mm) | 429–1175 | 430–648 | 267–1132 | 773–1265 |

Rainfall season | Summer | Summer | Winter | All-year |

**Table 2.**Examples of the impact that catchment shape, circularity, and elongation have on catchment response time in different area ranges.

Area Range (km^{2}) | Catchment | A (km^{2}) | F_{S} (Equation (1)) | R_{C} (Equation (2)) | R_{E} (Equation (3)) | T_{Px} (Equation (9), h) |
---|---|---|---|---|---|---|

300 ≤ A < 600 | U2H006 | 338 | 8.22 | 1.66 | 0.42 | 35.7 |

G1H008 | 394 | 4.49 | 1.32 | 0.87 | 10.8 | |

1000 ≤ A < 3000 | V2H001 | 1951 | 18.39 | 1.73 | 0.26 | 47.1 |

C5H012 | 2366 | 11.98 | 1.34 | 0.63 | 11.9 | |

A > 20,000 | V5H002 | 28,893 | 35.35 | 1.82 | 0.38 | 65.3 |

C5H014 | 31,283 | 28.12 | 1.48 | 0.61 | 56.6 |

**Table 3.**Correlation matrix between the observed time to peak values (T

_{Px}; Equation (9)) and geomorphological catchment characteristics.

Parameter | T_{Px} (h) | A (km^{2}) | P (km) | L_{H} (km) | L_{C} (km) | F_{S} (Equation (1)) | S_{2}:S_{CH}_{2} Ratio |
---|---|---|---|---|---|---|---|

T_{Px} (h) | 1.00 | - | - | - | - | - | - |

A (km^{2}) | 0.41 | 1.00 | - | - | - | - | - |

P (km) | 0.43 | 0.99 | 1.00 | - | - | - | - |

L_{H} (km) | 0.54 | 0.89 | 0.91 | 1.00 | - | - | - |

L_{C} (km) | 0.47 | 0.82 | 0.84 | 0.93 | 1.00 | - | - |

F_{S} (Equation (1)) | 0.51 | 0.87 | 0.89 | 0.98 | 0.98 | 1.00 | - |

S_{2}:S_{CH}_{2} Ratio | 0.48 | 0.18 | 0.19 | 0.27 | 0.21 | 0.25 | 1.00 |

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**MDPI and ACS Style**

Gericke, O.J. GIS Applications to Investigate the Linkage between Geomorphological Catchment Characteristics and Response Time: A Case Study in Four Climatological Regions, South Africa. *Water* **2019**, *11*, 1072.
https://doi.org/10.3390/w11051072

**AMA Style**

Gericke OJ. GIS Applications to Investigate the Linkage between Geomorphological Catchment Characteristics and Response Time: A Case Study in Four Climatological Regions, South Africa. *Water*. 2019; 11(5):1072.
https://doi.org/10.3390/w11051072

**Chicago/Turabian Style**

Gericke, Ockert J. 2019. "GIS Applications to Investigate the Linkage between Geomorphological Catchment Characteristics and Response Time: A Case Study in Four Climatological Regions, South Africa" *Water* 11, no. 5: 1072.
https://doi.org/10.3390/w11051072