# Flow-Type Landslides Analysis in Arid Zones: Application in La Chimba Basin in Antofagasta, Atacama Desert (Chile)

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## Abstract

**:**

## 1. Introduction

#### Study Area

**Figure 1.**Basins of the city of Antofagasta. The colors indicate a classification according to its hydrographic area.

**Figure 2.**Record of annual (blue bar) and daily (yellow circles) rainfall between the years 1918–2018 of the city of Antofagasta. The yellow triangles indicate rainfall with flooding and/or development of flow-type landslides. The red triangle indicates the hydrometeorological of the flow-type landslide event which occurred in Antofagasta city on 18 June 1991. This event is considered the largest landslide disaster registered in Chile. Information source: [33,34]. Rainfall records from the Dirección Meteorológica de Chile (DMC).

^{2}(Figure 3C), being considered one of the largest basins in the city of Antofagasta (Figure 1); in addition, according to Araya [35] and Chong et al. [36] there is previous evidence of activations, as in the hydrometeorological event of 1991. Despite the background presented, currently, the alluvial deposits of the mouth of the La Chimba basin have a significant number of urbanizations, located adjacent to the La Chimba dump and an aggregate extraction site. Likewise, real estate projects will be developed, projecting a significant population increase. Considering that this basin is gaining importance, there are no studies that estimate the type of hydrological response to possible rainfall events, nor an estimate of the possible areas of impact for urban areas and their future growth, nor the consideration of how flow-type landslides mitigation works.

## 2. Methodology

#### 2.1. Hydrometereological Characterization

_{L}) and detrital (Q

_{D}) calculation runoff flows were carried out for the different return periods.

#### 2.1.1. Pluviometric Analysis

_{D}) to be considered.

#### 2.1.2. Frequency Statistical Analysis and Maximum Flow Rates Calculation

_{c}) were obtained through a frequency statistical analysis and the calculation of exceedance and non-exceedance probabilities, in addition to rainfall for a specific return period (Tr). Next, the maximum liquid of flow-type landslide, through the IDF curves, frequency coefficient for a return period, design rainfall intensity for a return period (Tr—years), flow maximum liquid Q

_{L}(m

^{3}/s) using the rational method and the maximum debris flow (Q

_{D}) were calculated using the O’Brien and Julien (1997) method based on the concentration time calculated [37,38,39,40,41,42] (Appendix A).

#### 2.1.3. Flow-Type Landslide Mathematical Modeling

_{f}), volume of solids in the flow (V

_{d}) and average debris flow velocity (V

_{m}), among others (Appendix B).

^{2}). From these values, different scenarios were established for mathematical modeling, with the aim of representing different scenarios to obtain a flow of maximum, average and minimum fluidity (Table 1).

^{3}, where in this particular study a density of 2.0 gr/cm

^{3}is considered as a standard measure.

#### 2.2. Validation Analysis

#### 2.2.1. Soil Analysis

#### 2.2.2. Morphometric Analysis

#### 2.2.3. Basin Modeling

## 3. Results and Discussions

#### 3.1. Hydrometeorological Characterization

#### 3.1.1. Pluviometric Analysis

#### 3.1.2. Statistical Frequency Analysis

#### 3.1.3. Calculation of Maximum Flow Rates

^{Tr}) (mm). Table 5 and Table 6, and Figure 5 show the values obtained.

**Table 5.**Rainfall for different return periods and different duration. Pt

^{Tr}is the rain with a return period of Tr years and a duration of t hours on a millimeter scale. K is the correction coefficient. CDt is the duration coefficient for a period of t hours. CFt is the frequency coefficient for a return period of Tr years.

Duration (t) (Hours) | K | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 |
---|---|---|---|---|---|---|---|---|

CF | 0.53 | 0.83 | 1 | 1.18 | 1.42 | 1.6 | 1.78 | |

CDt | Rain P_{t}^{Tr} (mm) | |||||||

P_{t}^{Tr} Tr2 | P_{t}^{Tr} Tr5 | P_{t}^{Tr} Tr10 | P_{t}^{Tr} Tr20 | P_{t}^{Tr} Tr50 | P_{t}^{Tr} Tr100 | P_{t}^{Tr} Tr200 | ||

1 | 0.9 | 6.895 | 10.797 | 13.009 | 15.350 | 18.472 | 20.814 | 23.155 |

2 | 0.9 | 6.895 | 10.797 | 13.009 | 15.350 | 18.472 | 20.814 | 23.155 |

4 | 0.9 | 6.895 | 10.797 | 13.009 | 15.350 | 18.472 | 20.814 | 23.155 |

6 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

8 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

10 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

12 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

14 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

18 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

24 | 1 | 7.661 | 11.997 | 14.454 | 17.056 | 20.525 | 23.126 | 25.728 |

**Table 6.**Rainfall intensity (IPtTr) (mm/h) for different return periods of Tr years and for different durations of t hours.

Duration (t) (Hours) | Rain Intensity (mm/h) | ||||||
---|---|---|---|---|---|---|---|

IP_{t}^{Tr2} | IP_{t}^{Tr5} | IP_{t}^{Tr10} | IP_{t}^{Tr20} | IP_{t}^{Tr50} | IP_{t}^{Tr100} | IP_{t}^{Tr200} | |

1 | 6.895 | 10.797 | 13.009 | 15.350 | 18.472 | 20.814 | 23.155 |

2 | 3.447 | 5.399 | 6.504 | 7.675 | 9.236 | 10.407 | 11.578 |

4 | 1.724 | 2.699 | 3.252 | 3.838 | 4.618 | 5.203 | 5.789 |

6 | 1.277 | 1.999 | 2.409 | 2.843 | 3.421 | 3.854 | 4.288 |

8 | 0.958 | 1.500 | 1.807 | 2.132 | 2.566 | 2.891 | 3.216 |

10 | 0.766 | 1.200 | 1.445 | 1.706 | 2.052 | 2.313 | 2.573 |

12 | 0.638 | 1.000 | 1.205 | 1.421 | 1.710 | 1.927 | 2.144 |

14 | 0.547 | 0.857 | 1.032 | 1.218 | 1.466 | 1.652 | 1.838 |

18 | 0.426 | 0.666 | 0.803 | 0.948 | 1.140 | 1.285 | 1.429 |

24 | 0.319 | 0.500 | 0.602 | 0.711 | 0.855 | 0.964 | 1.072 |

**Figure 5.**Intensity-duration-frequency curves (IDF) based on the record of historical and current rainfall in Antofagasta city, as recommended for this type of analysis [40].

^{3}/s for La Chimba sub-basin, 35,544 m

^{3}/s for the Guanaco sub-basin and 110,294 m

^{3}/s for the area mouth.

#### 3.1.4. Flow-Type Landslide Mathematical Modeling

^{3}/s at 3 h of duration. Therefore, hydrographs were generated for the La Chimba basin and the Guanaco basin (Figure 6). In addition, it is calculated the Manning roughness coefficient (n) (see Table 8 and Table 9).

#### 3.2. Validation Analysis

#### 3.2.1. Soil Analysis

#### Geology

**Figure 7.**Debris flow impact maps for the La Chimba basin. Results of the mathematical modeling of the HEC-RAS software (

**A**), RAMMS software for maximum fluidity (

**B**), medium fluidity (

**C**) and minimum fluidity (

**D**) for a maximum debris flow of 110.29 m

^{3}in 1.5 h, representing the maximum intensity of the design event, with a return period of 200 years (Tr200) as the worst scenarios to represent. The red, orange, pink, dark green and light green colors represent from a materiality with null or almost null resistance to a high resistance to landslides such as flows. The bluish colors represent the maximum heights (meters) that debris flows can reach.

**Figure 8.**Debris flow impact map for the La Chimba basin in 3 dimensions. Results of RAMMS software modeling for maximum fluidity for a maximum debris flow of 110.29 m

^{3}in 1.5 h, representing the maximum intensity of the design rainfall event, with a return period of 200 years (Tr

_{200}). The red, orange, pink, dark green and light green colors represent from a materiality with null or almost null resistance to a high resistance to landslides such as flows. (

**A**) Overview. (

**B**) Details of the mouth of the La Chimba basin. The different yellow colorations of the flow indicate the maximum heights of the debris flow.

**Figure 9.**Geological units in the northern area of the city of Antofagasta. (

**i**) Geological map of the study area. (

**ii**) Geological map of La Chimba basin. Han. Anthropic deposits (Holocene). He. Active eolic deposit (Holocene). PlHa. alluvial deposits (Pleistocene–Holocene). PlHc. colluvial deposits (Pleistocene–Holocene) with (b) and without (a) sedimentary intercalations or covers of aeolian sands. PlHi. undifferentiated sedimentary deposits (Pleistocene–Holocene). PlHm. marine deposits (Pleistocene–Holocene). Ple. inactive aeolian deposits (Pleistocene). MPa. old alluvial and colluvial deposits (Upper Miocene–Pleistocene) with (b) and without (a) salt crust cover. Jln. La negra Formation (Lower Jurassic–Upper Jurassic) with (a) and without (b) regolith coverage. Jsmv. quartz diorite and Mantos de Varas tonalite (Upper Miocene–Pliocene) with (a) and without (b) regolith coverage. The delimitation of geological units underlying urban areas is approximate, due to the difficulty of access and visualization. Data from this work and modified from [23,53,54,55].

#### Granulometry

#### 3.2.2. Morphometric Analysis

_{c}), for its part, indicates that the La Chimba sub-basin has an oblong shape, distinct Guanaco, which presents it with an oval tendency, meaning that the latter will have a shorter concentration time than the La Chimba sub-basin (Appendix I).

_{c}).

#### 3.2.3. Basin Modeling

**Figure 11.**2D and 3D view of the methodological validation map with application in the Riquelme basin between the historical record of the impact zone due to flow-type landslide of the 1991 hydrometeorological event and the mathematical modeling with application of the same methodology of La Chimba basin modeling.

## 4. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A. Methodological Summary with Its Equations Used, Corresponding to the Hydrometeorological Analysis for the Calculation of Maximum Liquid and Debris Flows for La Chimba Basin, Antofagasta (Chile)

Hydrometeorological Characterization | |||
---|---|---|---|

Analysis | Method | Method—Equation | Description |

Statistical frequency analysis | Probabilities of non-excess | $P\left(X<x\right)={e}^{-{e}^{\frac{-\left(x-u\right)}{\alpha}}}$ | P(X < x) is the probability of non-excess, P(X > x) is the probability of excess, e is the natural number, Tr is the return period, x are the recorded rainfall events and α and u are eigenmetric parameters of the expression. ẋ is the arithmetic mean of the samples, S_{x} is the standard deviation of the samples and σ_{y} and μ_{y} are values that are a function of the total number of total samples [37,38,39]. |

Probabilities of excess | $P\left(X>x\right)=1-{e}^{-{e}^{-\frac{\left(x-u\right)}{\alpha}}}=\frac{1}{{T}_{r}}$ | ||

Parameters of the expression | $\alpha =\frac{{S}_{x}}{{\sigma}_{y}}$ | ||

Rainfall for a specific return period (mm) | $\begin{array}{c}u=\dot{\mathrm{x}}-{\mu}_{y}\times \alpha \\ {P}^{Tr}=-Ln\left(-Ln\left(1-\frac{1}{{T}_{r}}\right)\right)\times \alpha +\mu \end{array}$ | P^{Tr} is the rainfall event recorded (mm) for a specific return period (Tr), Ln is the natural logarithm and α—μ are parameters of the equation described above [37]. | |

Calculation of maximum flows | IDF Curves | ${P}_{t}{}^{Tr}=K\times C{D}_{t}\times C{F}_{T}\times {P}^{Tr10}$ | Pt^{Tr} is the rain with return period Tr years and duration of t hours, P^{Tr10} is the maximum daily rainfall (24 h) with 10 years of return period, CDt is the duration coefficient for t hours, CFT is the frequency coefficient for T years of return period and K is the correction coefficient for the maximum rainfall P^{Tr10} measured between 8 am and 8 am with respect to the 24 rainiest hours of the storm, which, according to the Manual of Roads [38], adopts a value of 1.1. CFT is the frequency coefficient for a return period T. Pt^{Tr} is the rainfall of duration t and return period of T years. Pt^{Tr10} is rainfall of duration t and return period of 10 years. The duration coefficients and frequency coefficients for cities in Chile with the same return period were extracted from DICTUC [59]. |

Frequency coefficient for a return period (CD_{t}) | $C{D}_{t}=\frac{{P}_{t}{}^{Tr10}}{{P}_{24}{}^{Tr10}}$ | ||

Design rainfall intensity for a return period Tr (años) | $I{P}_{t}{}^{{T}_{r}}=\frac{{P}_{t}{}^{{T}_{r}}}{t}$ | IP_{t}^{Tr} is the intensity of rainfall for a return period of Tr years and for a duration of t hours, IP_{t}^{Tr} is the rainfall for a return period of Tr years and for a duration of t hours and t is the duration in hours. From these data we proceed to graph the IDF curve [59]. | |

Rational Method. Maximum liquid flow rate Q_{L} (m^{3}/s) | ${Q}_{L}=\frac{C\times i\times {A}_{a}}{3.6}$ | Calculation by generating a hydrogram from the rational method and empirical expression. The calculation of several parameters is required including the runoff coefficient (C) (dimensionless, where 0 ≤ C ≤ 1), which includes basin characteristics such as: relief, infiltration, vegetation cover and surface storage [40]. | |

Concentration time T_{c} (minutos) | ${T}_{c}=0.95\times {\left(\frac{{({L}_{cp})}^{3}}{H}\right)}^{0.385}$ | Expression of California Highways [41], ideal for mountain basins and arid character, as in the case under study, in which T_{c} is the concentration time (hours), L_{cp} is the length of the main channel (km) and H corresponds to the unevenness from the starting point of the channel to the mouth point (m). | |

O’Brien and Julien Method (1997) [60] Detritic Maximum Flow Rate (Q_{D}) | ${Q}_{D}={Q}_{L}\times BF={Q}_{L}\times \frac{1}{1-{C}_{v}}$ | Q_{D} is the maximum detrital flow rate (m^{3}/s), Q_{L} is the liquid runoff flow (m^{3}/s) and BF is the factor called bulking factor, where C_{v} is the volumetric concentration of solids, whose value is extracted from the study of Ayala et al. [42] |

## Appendix B. Some Outstanding Equations that Mathematically Govern the HEC-RAS and RAMMS Software, in Addition to the Equations for Calculating the Parameters Required to Be Inserted

Hydrometeorological Characterization | |||
---|---|---|---|

Software | Method | Method—Equation | Description |

HEC-RAS v6.1 | Flow heights in a non-permanent flow regime | ${Q}_{D}=\left(\frac{{A}_{h}}{{n}_{D}}\right)\times {R}_{h}{}^{\frac{2}{3}}\times {S}_{f}{}^{\frac{1}{2}}$ | Q_{D} (m^{3}/s) corresponds to the detrital flow, A_{h} (m^{2}) is the wet area or cross-sectional area of the detrital flow, R_{h} (m) is the hydraulic radius associated with the different cross-sections considered, respectively, n_{D} corresponds to the Manning coefficient for a detrital flow which depends on the roughness of the walls and S_{f} represents the slope of the potential line [61]. |

Cowan Methodology—Manning Roughness Coefficient (n_{D}) | ${n}_{D}=\left({n}_{b}+{n}_{1}+{n}_{2}+{n}_{3}+{n}_{4}\right)\times m$ | n_{b} describes the quality of the material present in the floor of the ravine, n_{1} considers the effect of superficial irregularities, n_{2} quantifies the variations in shape and size of the different cross-sections, n_{3} is the relative effect of obstructions in the channel, n_{4} quantifies the density of vegetation and m is a corrective factor that considers the degree of sinuosity or meander of the channel. For the case study, n_{b} was determined by granulometric data from soil samples from the respective streams [62]. | |

RAMMS v1.7.20 | Total friction (S_{f}) | ${S}_{fx}={n}_{{U}_{x}}[\mu {g}_{Z}H+\frac{g{\left|\left|U\right|\right|}^{2}}{\xi}]$ | Flow height H(x, y, t) (m) and mean velocity U(x, y, t) (m/s). In turn, consider a total friction (S_{f}) in the following equation. n_{Ux} and n_{Uy} are the directional unit velocity vectors in the x and y directions, respectively. The total basal friction in the Voellmy–Salm model is divided into a velocity-independent Coulomb dry friction coefficient μ (M_{u}) and a velocity-dependent turbulent friction coefficient ξ (X_{i}) (m/s^{2}) [63,64,65]. |

${S}_{fy}={n}_{{U}_{y}}[\mu {g}_{Z}H+\frac{g{\left|\left|U\right|\right|}^{2}}{\xi}]$ | |||

Takahashi Method (1991)—Volume of solids in the flow (V_{d}) | ${V}_{d}=1500\times \left[\frac{{Q}_{D}}{1-{C}_{V}}\right]$ | V_{d} is the Volume of solids in the flow (m^{3}), Q_{D} is the maximum detrital flow (m^{3}/s) and C_{V} corresponds to the volumetric concentration (-). | |

Mean detrital flow rate (V_{m}) (m/s) | $Vm=\frac{1}{{n}_{D}}\times {R}^{\frac{2}{3}}\times {i}^{\frac{1}{2}}$ | V(h) is the average flow rate in m/s, as a function of the water height h, R corresponds to the hydraulic radius of the section considered (m), n represents the Manning roughness coefficient and i is the slope of the water line (m/m) [40]. |

## Appendix C. Statistical Parameters Used in the Granulometric Analysis of La Chimba Basin

Name | Method—Equation | Description |
---|---|---|

Gradation of the soil. Coefficient of uniformity (C_{u}) and Coefficient of curvature (C_{c}) [66] | ${C}_{u}=\frac{{D}_{60}}{{D}_{10}}$ ${C}_{c}=\frac{{\left({D}_{30}\right)}^{2}}{{D}_{10}\times {D}_{60}}$ | The uniformity coefficient (C_{u}) is the extension of the granulometric distribution curve. The coefficient of curvature (C_{c}) gives information regarding the distribution of intermediate sizes. Both coefficients are used as criteria in the Unified Soil Classification System (U.S.C.S.) |

Hydraulic conductivity coefficient (K) [67] | $K=\left(8.64\times Ca\times ({\left(D10\right)}^{2}\right)\xf724$ | K is the hydraulic conductivity (cm/h), D10 is the effective size of the sediments (mm) (10% smaller and 90% larger) and Ca is a coefficient that depends on grain size and uniformity [39]. The effective diameter is calculated directly from the cumulative frequency graph. The factor of 8.64 allows us to enter the value of D10 in mm and we obtain the result of K in m/day. |

Average Graphic Size (Mz) [68] | $Mz=\frac{\left(\varnothing 16+\varnothing 50+\varnothing 75\right)}{3}$ | It corresponds to the measure of the mean size of the sample in phi units (Φ). Mz corresponds to the mean size of the graph on a phi scale (Φ) and Φ16, Φ50, Φ75 and Φ5 correspond to percentiles with their corresponding percentage. The final result will be evaluated according to the Udden-Wentworth classification and will be indicative of the average kinetic energy of the current. |

Inclusive graphical standard deviation (Φi) [68] | $\varnothing i=\frac{\varnothing 84-\varnothing 16}{4}+\frac{\varnothing 95-\varnothing 5}{6.6}$ | A measure of spread, indicating how far values may be from the average (mean). Φi is the inclusive standard deviation, Φ84, Φ16, Φ95 and Φ5 are percentiles with their corresponding percentage. It provides information on the level of selection of the sample and therefore it is a very sensitive index to define the fluidity of the transport and sedimentation medium. |

Degree of inclusive graphic skewness (Ski) [68] | $Ski=\frac{\varnothing 16+\varnothing 84-\left(2\times \varnothing 50\right)}{2\times \left(\varnothing 84-\varnothing 16\right)}+$ $\frac{\varnothing 5+\varnothing 95-\left(2\times \varnothing 50\right)}{2\times \left(\varnothing 95-\varnothing 5\right)}$ | Ski is the degree of inclusive graphic skewness, Φ5, Φ16, Φ50, Φ84 and Φ95 are percentiles with their corresponding percentage. |

Measurement of graphic Kurtosis (K_{G}) [68] | ${K}_{G}=\frac{\varnothing 95-\varnothing 5}{2.44\times \left(\varnothing 75-\varnothing 25\right)}$ | Many curves designated as “normal” by the skewness measure are markedly abnormal when calculated by kurtosis. If the central part of the curve has better selection than the extremes, the curve is leptokurtic, while if the selection is better at the extremes, the curve is platychortic. |

Mode [46] | - | There may be one or more modes giving rise to unimodal (one), bimodal (two) or multimodal (greater than two) distributions, respectively. In the latter case, the most abundant is called the main mode and the other modes are secondary. |

## Appendix D. Methodological Summary Corresponding to the Morphometric Analysis of La Chimba Basin, Antofagasta (Chile)

Form Parameters | ||
---|---|---|

Name | Equation or Method | Description |

Basin Area (A) [km^{2}] | Geographic information system (GIS) | A measure of the surface area of a basin, defined as the orthogonal projection of the entire drainage area of a runoff system flowing directly or indirectly into the basin [56] |

Basin Perimeter (P) [km] | It is defined as the measurement of the watershed envelope line, by the topographic watershed [51] | |

Axial Length (A_{l}) [km] | Distance in a straight line between the mouth and the farthest point on the perimeter (P) of the basin, which in some cases coincides with the length of the main course [51] | |

Length of the main channel (Lc) [km] | Represents the length of the channel over its entire course (km), including all the sinuosity of the channel. | |

Form Factor (F) [69] | $F=\frac{A\left(k{m}^{2}\right)}{{\left(Lc\right)}^{2}\left(km\right)}$ | It is defined as the ratio between the area (A) and the length of the drainage basin (L_{c}). |

Compactness Factor (K_{c}) [70] | ${K}_{c}=0.28\times \left(\frac{P\left(km\right)}{\sqrt{A\left(k{m}^{2}\right)}}\right)$ | This factor is the oldest one, expressing the relationship between the perimeter of the drainage basin and that of a circle of equal area (equivalent circle); thus, the higher the coefficient, the more distant the shape of the basin will be with respect to the circle. P represents the perimeter (km) and A the area (km^{2}) of the Macul basin. |

Drainage System Parameters | ||

Name | Equation or method | Description |

Drainage order (n) [57] | Geographic information system (GIS) | Horton [69] suggests a hierarchization of streams according to order number as a measure of the branching of the main channel in a basin. This system is dimensionless and was later improved and slightly modified by Strahler [57], indicating that a stream may have one or more segments. |

Bifurcation ratio (B_{r}) [57] | ${B}_{r}=\frac{{n}_{i}}{{n}_{i+1}}$ | It is the ratio between the total number of drains of a certain order (n_{i}) and the total number of drains of the next higher order (n_{i}_{+1}). |

Length Ratio (L_{r}) [57] | ${L}_{r}=\frac{{L}_{i}\left(km\right)}{{L}_{i-1}\left(km\right)}$ | The ratio of the average length of a certain order of drainage (L_{i}) of the average length of the order of drainages that is immediately lower (L_{i}_{−1}). |

Drainage network density (Dd) [71] [1/km] | $Dd=\frac{\Sigma {L}_{i}\left(km\right)}{A\left({km}^{2}\right)}$ | Quotient between the total length of the channels of all of the orders that make up the river system of the basin (∑L_{i}) and the total area of the basin (A). |

Drainage Frequency (F) [72] [1/km^{2}]. | $F=\frac{{n}_{t}}{A\left({km}^{2}\right)}$ | It is defined as the quotient between the total number of river courses (n_{t}) and the area of the basin (km^{2}). When obtained, it quantifies the potential for any drop of water to find a channel in within an arbitrary timeframe. |

Drainage hierarchy (J) | Geographic information system (GIS) | Represents the highest drainage order, obtained using Strahler’s [57] drainage order methodology. |

Relief Parameters | ||

Name | Equation or method | Description |

Absolute elevation difference (H) [ m a.s.l.] | $H=\left(HM-Hm\right)$ | Corresponds to the difference between the maximum elevation (HM) and the minimum elevation (Hm), measured in meters above sea level (m a.s.l.). |

Average slope of the basin (Sm) [%] | Geographic information system (GIS) | The average slope of a watershed is directly related to the degradation process to which a watershed is subjected [73]. |

Hypsometric curve [57] | Geographic information system (GIS) and mathematical calculations by calculating relative elevation and relative area, and then applying the results to a graph | The hypsometric curve suggested by Langbein et al. [74] graphically represents the elevations of the terrain as a function of the corresponding surfaces. According to Strahler [57], the importance of this relationship lies in the fact that it is an indicator of the state of dynamic equilibrium of the basin, so the basin can be in a state of youth (disequilibrium), in a state of maturity (equilibrium) or at intermediate levels. |

Complementary Parameters | ||

Name | Equation or method | Description |

Torrentiality coefficient (T_{c}) [73] (1/km^{2}) | ${T}_{c}=\frac{{n}_{1}}{A\left({km}^{2}\right)}$ | Index that measures the degree of torrentiality of the basin, by means of the ratio of the number of drainages of order 1 (n_{1}) with respect to the total area of the basin (A). |

Potentiality index (P_{i}) [75] | ${P}_{i}=\frac{\left(Dd\left(\frac{1}{km}\right)+F\left(\frac{1}{{km}^{2}}\right)+J\right)}{A\left({km}^{2}\right)}$ | It determines the location of erosion and accumulation zones in a watershed; its determination is important. A high P_{i} value will reveal that in a specific hydrological basin there is accumulation of debris, which could be transported if high rainfall occurs, as to generate an alluvial event [76] |

## Appendix E. Base Data and Comparative Data from Meteorological Stations with Available Records for the City of Antofagasta

Institution | Name Estation | Coordinates | Measurement Height (m a.s.l.) | Range of Years with Data Availability | Rainfall Record—Orographic Effect on the Records—Event 1991 | Distance in Relation to the Study Area (km) | Differences between the Average Maximum Rainfall Measurements in 24 h per Year between 1968 and 2018 |
---|---|---|---|---|---|---|---|

(DMC) | Portezuelo | 23°42′ S 70°24′ W | 550 | 1904–1944 (40 years) | 14.1 | 14.2 | 1.53 (DMC/UCN-DGA) |

Cerro Moreno | 23°27′ S 70°26′ W | 119–137 | 1946–2018 (72 years) | ||||

(DMC) | Universidad Católica del Norte (UCN) | 23°41′ S 70°25′ W | 30 | 1968–2018 (50 years) | 42.0 | 17.5 | 1.56 (DGA—DMC/Cerro Moreno) |

(DGA) | DGA | 23°35′ S 70°23′ W | 50 | 1978–2018 (40 years) | 17.0 | 5.5 | 2.17 (DMC/UCN—DMC/Cerro Moreno) |

## Appendix F. Area and Description of the Geological Units Present in the La Chimba Basin

Name | Area [km^{2}] | Description |
---|---|---|

La Negra Formation Jln (a) (Lower Jurassic–Upper Jurassic) | 15,725 | Andesitic lavas and pyroxene andesites of gray to greenish gray colors with aphanitic, porphydic, brechosal and tonsilloidal textures with subordinate levels of sedimentary gaps and medium grain sandstones. It emerges as a continuous strip of direction NNE—SSW forming a monoclinal sequence with general attitude of N5°–10° W/55°–70° W, which reaches a minimum potential of 5050 m. |

La Negra Formation Jln (b) (Lower Jurassic–Upper Jurassic) | 5902 | |

Alluvial deposits PlHa (Pleistocene–Holocene) | 2111 | Gravels and sands unconsolidated to slightly cemented that make up the filling of the active ravines and the alluvial fans of the Cordillera de la Costa. The gravels are clastosoportadas with poorly graded clasts and the matrix consists mainly of coarse sands to silts. They present horizontal and locally paleochannel stratification, grain-decreasing tendencies and imbrications. |

Ancient alluvial and colluvial deposits MPla (b) (Upper Miocene–Pleistocene) | 0.404 | Unconsolidated to semi-consolidated gravels and sands, distributed in the eastern sector of the study area including the La Chimba basin. They represent continental deposits of piedmont and mud flows originated by gravitational flows and sporadic water contributions under a desert climate where they form cones of medium to strong slope. |

Ancient alluvial and colluvial deposits MPla (a) (Upper Miocene–Pleistocene) | 0.327 | |

Coluvial deposits PlHc (Pleistocene–Holocene) | 0.242 | Poorly stratified gravels and sands, unconsolidated to moderately cemented, in centimeter to metric layers distributed on the slopes of steep slopes of the Costa Mountain Range. The gravels are clastosoportadas to matrix supported. The clasts have a poor selection, they are angular with low sphericity and the matrix are fine gravels and coarse sands of grayish brown tones. The sands are coarse in size with regular to a good selection. |

## Appendix G. Granulometric Results for the La Chimba and Guanaco Sub-Basins. The Values in Gray Are Reference Values since They Were Not Used to Calculate the Parameter in Question

La Chimba Sub-Basin | ||||||
---|---|---|---|---|---|---|

Samples Codes → | LCHN-1 | LCHN-6 | ||||

Statistical Parameters | Opening (mm) | Aperture | Result | Opening (mm) | Aperture | Result |

Phi (Φ) | Phi (Φ) | |||||

Coefficient of uniformity (C_{u}) | 29.167 | −4.866 | Very well graded | 27.500 | −4.781 | Very well graded |

Coefficient of curvature (C_{c}) | 1.339 | −0.421 | Well graded | 1.237 | −0.307 | Well graded |

Hydraulic Conductivity Coefficient (K) [cm/h] | 41.472 | SP-SW (U.S.C.S) | 41.472 | SP-SW (U.S.C.S) | ||

(cm/h) | (cm/h) | |||||

Average Chart Size (Mz) | 2.378 | −1.250 | Granule, flow and average energy of the current | 2.351 | −1.233 | Granule, flow and average energy of the current |

Inclusive graph standard deviation (Φi) | 0.149 | 2.748 | Very poorly selected. Low fluidity and high energy current | 0.149 | 2.748 | Very poorly selected. Low fluidity and high energy current |

Degree of inclusive graphic asymmetry (Ski) | 0.892 | 0.165 | Asymmetrical towards fine | 0.9011 | 0.150 | Asymmetrical towards fine |

Measurement of graphical Kurtosis (KG) | 0.520 | 0.943 | Mesokurtic | 0.501 | 0.998 | Mesokurtic |

Mode | −1; 3.6 | Bimodal: Granules—fine sands | −1; 3.6 | Bimodal: Granules—fine sands | ||

Unified Soil Classification System (U.S.C.S.) | SW | Well-graduated sands, sands with gravel, with few or no fines | SW | Well-graduated sands, sands with gravel, with few or no fines | ||

SM | Silty sands, poorly graded sand and silt mixtures | SM | Silty sands, poorly graded sand and silt mixtures | |||

Guanaco Sub-basin | ||||||

Samples codes → | LCHS-1 | LCHS-7 | ||||

Coefficient of uniformity (C_{u}) | 25.000 | −4.644 | Very well graded | 33.929 | −5.084 | Very well graded |

Coefficient of curvature (C_{c}) | 1.210 | −0.275 | well graded | 2.350 | −1.232 | well graded |

Hydraulic Conductivity Coefficient (K) [cm/hr] | 115.2 | SP-SW (U.S.C.S) | 56.448 | SP-SW (U.S.C.S) | ||

(cm/h) | (cm/h) | |||||

Average Chart Size (Mz) | 3.523 | −1.817 | Small pebble, flow and average energy of the current | 3.287 | −1.717 | Small pebble, flow and average energy of the current |

Inclusive graph standard deviation (Φi) | 0.150 | 2.736 | Very poorly selected. Low fluidity and high energy current | 0.169 | 2.563 | Very poorly selected. Low fluidity and high energy current |

Degree of inclusive graphic asymmetry (Ski) | 1.060 | −0.084 | Almost asymmetrical | 0.802377 | 0.318 | Very asymmetrical towards fine |

Measurement of graphical Kurtosis (KG) | 0.484 | 1.045 | mMesokurtic | 0.453 | 1.142 | Leptokurtic |

Mode | - | −4.6; 0.2; 3.6 | Multimodal: guijarro pequeño, arena muy gruesa y arena fina | - | −1; 3.6 | Bimodal: granules and fine sand |

Unified Soil Classification System (U.S.C.S.) | SW | Well-graduated sands, sands with gravel, with few or no fines | SW | Well-graduated sands, sands with gravel, with few or no fines | ||

SM | Silty sands, poorly graded sand and silt mixtures | SM | Silty sands, poorly graded sand and silt mixtures |

## Appendix H. Granulometric Results for the Mouth Area. The Values in Gray Are Reference Values Since They Were Not Used to Calculate the Parameter in Question

Basin Mouth | |||
---|---|---|---|

Samples Code | LCHCP-2 | ||

Statistical Parameters | Opening (mm) | Aperture | Result |

Phi (Φ) | |||

Coefficient of uniformity (C_{u}) | 25.000 | −4.644 | Very well graded |

Coefficient of curvature (C_{c}) | 1.210 | −0.275 | Well gradado |

Hydraulic Conductivity Coefficient (K) [cm/hr] | 165.888 | SP-SW (U.S.C.S) | |

(cm/hr) | |||

Average Chart Size (Mz) | 3.647 | −1.867 | Small pebble, flow and average current energy |

Inclusive graph standard deviation (Φi) | 0.223 | 2.164 | Very poorly selected. Low fluidity and high energy current |

Degree of inclusive graphic asymmetry (Ski) | 1.226 | −0.294 | Asymmetrical towards thick |

Measurement of graphical Kurtosis (KG) | 0.653 | 0.615 | Very platykurtic |

Mode | 25.4, −0.84, −0.08 | - | Multimodal: small pebble, granules and fine sand |

Unified Soil Classification System (U.S.C.S.) | SW | Well-graduated sands, sands with gravel, with few or no fines | |

SM | Silty sands, poorly graded sand and silt mixtures | ||

Samples code | LCHCP-11 | ||

Statistical parameters | Opening (mm) | Aperture | Result |

Phi (Φ) | |||

Coefficient of uniformity (C_{u}) | 36.364 | −5.184 | Very well graded |

Coefficient of curvature (C_{c}) | 0.364 | 1.459 | Poorly graded |

Hydraulic Conductivity Coefficient (K) [cm/h] | 34.848 | SP-SW (U.S.C.S) | |

(cm/h) | |||

Average Chart Size (Mz) | 1.866 | −0.900 | Small pebble, flow and average current energy |

Inclusive graph standard deviation (Φi) | 0.202 | 2.308 | Very poorly selected. Low fluidity and high energy current |

Degree of inclusive graphic asymmetry (Ski) | 11.349 | −0.183 | Asymmetrical towards thick |

Measurement of graphical Kurtosis (KG) | 0.748 | 0.419 | Very platykurtic |

Mode | 25.4, −4.75, −2, −0.08 | - | Multimodal: small pebble, granules and fine sand |

Unified Soil Classification System (U.S.C.S.) | SP | Well-graduated sands, sands with gravel, with few or no fines | |

- | - | ||

Samples code | LCHCP-18 | ||

Statistical parameters | Opening (mm) | Aperture | Result |

Phi (Φ) | |||

Coefficient of uniformity (C_{u}) | 45.000 | −5.492 | Very well graded |

Coefficient of curvature (C_{c}) | 1.800 | −0.848 | Well gradado |

Hydraulic Conductivity Coefficient (K) [cm/h] | 115.200 | SP-SW (U.S.C.S) | |

(cm/h) | |||

Average Chart Size (Mz) | 5.528 | −2.467 | Small pebble, flow and average current energy |

Inclusive graph standard deviation (Φi) | 0.239 | 2.065 | Very poorly selected. Low fluidity and high energy current |

Degree of inclusive graphic asymmetry (Ski) | 0.91581265 | 0.127 | Asymmetrical towards thick |

Measurement of graphical Kurtosis (KG) | 0.670 | 0.578 | Very platykurtic |

Mode | 25.4, −9.5, −4.75, −0.08 | - | Multimodal: small pebble, granules and fine sand |

Unified Soil Classification System (U.S.C.S.) | GW | Well-graded gravel, mixture of gravel and sand with few or no fines | |

GM | Silty gravels, poorly graduated mixtures of gravel, sand and silt |

## Appendix I. Shape Parameters, Whose Value Is Related to Its Meaning

Form Parameters | ||||||||
---|---|---|---|---|---|---|---|---|

Zone | A | P | L_{A} | A_{P} | AA | L_{CP} (km) | F | Kc |

(km^{2}) | (km) | (km) | (km) | (km^{2}) | ||||

La Chimba basin | 24.710 | 23.594 | 7.056 | 3.502 | 11.120 | 7.715 | 0.415 | 1.329 |

La Chimba sub-basin | 17.217 | 21.000 | 7.056 | 2.440 | 7.748 | 7.715 | 0.289 | 1.417 |

Guanaco sub-basin | 7.493 | 12.715 | 4.252 | 1.762 | 3.372 | 4.780 | 0.328 | 1.301 |

^{2}). P. Perimeter (km). THE. Axial length (km). AP. Average width (km). PCL. Length of the main channel (km). F. Horton form factor (dimensionless). Kc. Compactness factor (dimensionless).

## Appendix J. Drainage Network Parameters, Whose Value Is Related to Their Meaning

Drainage Network Parameters | |||||
---|---|---|---|---|---|

Zona | Branch Relationship (R_{b}) | Length Ratio (RL) | Densidad de Drenajes (D_{d}) | Frecuencia de Drenajes (F_{d}) | Jerarquía de Drenajes (J) |

Cuenca La Chimba | 5.179 | 0.519 | 10.701 | 71.267 | 6 |

Mountain basins. Typical river system. Steep slopes with rapid runoff formation and minor flood maxims | May present high concentrations of runoff along the main channel | Very well drained basin. High volume generation runoff velocities | High probability that the rainwater drop will find a drain | ||

Subcuenca La Chimba | 5.729 | 0.547 | 10.925 | 70.744 | 5 |

Mountain basins. Typical river system. Steep slopes with rapid runoff formation and minor flood maxims | May present high concentrations of runoff along the main channel | Sub-basin very well drained. Large volume generation and runoff velocities | High probability that the rainwater drop will find a drain | ||

Subcuenca Guanaco | 4.747 | 0.572 | 10.188 | 72.467 | 5 |

Mountain basins. Typical river system. Steep slopes with rapid runoff formation and minor flood maxims | May present high concentrations of runoff along the main channel | Sub-basin very well drained. Large volume generation and runoff velocities | Very high probability that the rainwater droplet will find a drain |

_{b}. Bifurcation relation. RL. length ratio. D

_{d}. Density of the drainage network. F

_{d}. Drain frequency. J. Hierarchy of drains.

## Appendix K. Complementary Parameters, Whose Values Are Related to Their Meaning

Supplementary Parameters | ||
---|---|---|

Zone | Torrentiality Coefficient (Ct) | Potentiality Index (IP) |

La Chimba basin | 57.790 | 3.6 |

La Chimba sub-basin | 56.862 | 5.092 |

Guanaco sub-basin | 59.923 | 11.831 |

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**Figure 3.**Location map. (

**A**) Indicates the location of Chile on a country scale. (

**B**) Indicates the location of the city of Antofagasta, Antofagasta Region. (

**B.2**) Indicates the location of the city of Antofagasta with a 3D view. (

**C**) It is the location of the La Chimba basin with a 3D view. (

**D**) It is the location of the Riquelme basin with a 3D view (validation method).

**Figure 4.**Location of pits and soil samples in the study area. The white points and codes indicate samples from the mouth area, light blue points indicate Guanaco sub-basin samples and yellow colors indicate La Chimba sub-basin samples. The brown color represents the Municipality Dump. The purple area represents a sedimentary material extraction zone and ground modification.

**Figure 6.**Triangular flood hydrograph for La Chimba basin. Represents the debris flow variation rates as a function of the rainfall event duration. The left figure indicates the La Chimba sub-basin (orange line) and the Guanaco sub-basin (purple line) unit hydrograph. The right figure indicates the unit hydrograph of the La Chimba basin mouth.

**Table 1.**Values considered for flow-type landslide mathematical models with variation in the state of fluidity. Source: values from [43].

Fluidity | Parameter | Value |
---|---|---|

Maximum fluidity | ξ (m/s^{2}) | 500 |

µ | 0.05 | |

Medium fluidity | ξ (m/s^{2}) | 350 |

µ | 0.125 | |

Minimum fluidity | ξ (m/s^{2}) | 200 |

µ | 0.2 |

**Table 2.**Calculation of the probabilities of exceedance, non-exceedance and Return Period (Tr) for maximum annual rainfall according to the Gumbel method. A. Years of rainfall: 1978, 1985, 1988, 1990, 1993, 1997, 1998, 1999, 2001, 2003, 2007, 2008, 2010, 2013 and 2018. Tr. Return period, which is inversely proportional to the probability of exceedance (P(X < x) %). Source: Data extracted from the Dirección General de Aguas (DGA) [42,52].

Data Ordered from Highest to Lowest (Rainfall) | Gumbel Distribution for Extreme Values | |||||
---|---|---|---|---|---|---|

Date | Maximum Daily Rainfall Events (mm) | Gumbel Distribution Probability of Non-Exceedance (P(X < x)) | Gumbel Distribution Probability of Non-Exceedance (P(X < x)%) | Gumbel Distribution Exceedance Probability (P(X < x)) | Gumbel Distribution Exceedance Probability (P(X < x)%) | Return Period (Tr) (Years) |

24 March 2015 | 31.50 | 0.9957 | 99.57% | 0.0043 | 0.43% | 230.1945 |

6 June 2017 | 20.50 | 0.9711 | 97.11% | 0.0289 | 2.89% | 34.5495 |

17 June 1991 | 17.00 | 0.9475 | 94.75% | 0.0525 | 5.25% | 19.0519 |

28 July 1987 | 13.20 | 0.9010 | 90.10% | 0.0990 | 9.90% | 10.1000 |

29 August 2006 | 11.50 | 0.8693 | 86.93% | 0.1307 | 13.07% | 7.6525 |

24 June 2016 | 6.70 | 0.7246 | 72.46% | 0.2754 | 27.54% | 3.6312 |

8 July 2011 | 6.10 | 0.6994 | 69.94% | 0.3006 | 30.06% | 3.3271 |

13 January 1983 | 6.00 | 0.6951 | 69.51% | 0.3049 | 30.49% | 3.2795 |

27 August 2002 | 3.80 | 0.5869 | 58.69% | 0.4131 | 41.31% | 2.4209 |

27 August 1982 | 3.50 | 0.5705 | 57.05% | 0.4295 | 42.95% | 2.3280 |

28 May 1992 | 3.00 | 0.5422 | 54.22% | 0.4578 | 45.78% | 2.1841 |

7 June 1984 | 2.00 | 0.4828 | 48.28% | 0.5172 | 51.72% | 1.9334 |

31 May 2000 | 1.80 | 0.4705 | 47.05% | 0.5295 | 52.95% | 1.8886 |

20 July 2009 | 1.60 | 0.4581 | 45.81% | 0.5419 | 54.19% | 1.8455 |

12 September 2014 | 1.40 | 0.4457 | 44.57% | 0.5543 | 55.43% | 1.8040 |

18 May 1986 | 1.00 | 0.4205 | 42.05% | 0.5795 | 57.95% | 1.7257 |

20 May 1995 | 1.00 | 0.4205 | 42.05% | 0.5795 | 57.95% | 1.7257 |

20 July 1994 | 0.80 | 0.4079 | 40.79% | 0.5921 | 59.21% | 1.6888 |

5 August 1981 | 0.70 | 0.4015 | 40.15% | 0.5985 | 59.85% | 1.6709 |

26 March 1979 | 0.50 | 0.3888 | 38.88% | 0.6112 | 61.12% | 1.6361 |

20 August 1989 | 0.50 | 0.3888 | 38.88% | 0.6112 | 61.12% | 1.6361 |

29 August 1996 | 0.50 | 0.3888 | 38.88% | 0.6112 | 61.12% | 1.6361 |

27 October 1980 | 0.40 | 0.3824 | 38.24% | 0.6176 | 61.76% | 1.6192 |

25 April 2005 | 0.40 | 0.3824 | 38.24% | 0.6176 | 61.76% | 1.6192 |

26 July 2004 | 0.10 | 0.3632 | 36.32% | 0.6368 | 63.68% | 1.5705 |

A | 0.00 | 0.3569 | 35.69% | 0.6431 | 64.31% | 1.5549 |

**Table 3.**Results of the parameters of the Gumbel method equation. Where α and u are parameters of the expression and σ

_{y}and µ

_{y}are values that are based on the number of data or total samples, which are given based on Sánchez [37].

Number of Data (n) | Mean (Average) (Ẋ) | Trend | Standard Deviation (S_{x}) | σ_{y} | μ_{y} | α | u |
---|---|---|---|---|---|---|---|

41 | 3.3 | 0.000 | 6.576 | 1.1413 | 0.5436 | 5.7622 | 0.1726 |

**Table 4.**Rainfall for different specific return periods (Tr). P

^{Tr}(mm) maximum daily rainfall in a return period of “x” years.

Tr | 1/P^{Tr} | 1-1/Tr | P^{Tr} (mm) |
---|---|---|---|

2 | 0.5 | 0.5 | 2.284 |

5 | 0.2 | 0.8 | 8.815 |

10 | 0.1 | 0.9 | 13.140 |

20 | 0.05 | 0.95 | 17.287 |

50 | 0.02 | 0.98 | 22.656 |

100 | 0.01 | 0.99 | 26.679 |

200 | 0.005 | 0.995 | 30.688 |

**Table 7.**Design rainfall intensity (mm/h) and debris flows (m

^{3}/s) as a function of concentration time (T

_{c}) (h) in the basin.

Result | ||||
---|---|---|---|---|

Return Period (Tr) (Años) | Design Rain Intensity (i) (mm/h) | La Chimba Sub-Basin | Guanaco Sub-Basin | Total Detrital Flow (Q _{DT}) (m^{3}/s) |

Debris Flow (Q_{D}) (m^{3}/s) | Debris Flow (Q_{D}) (m^{3}/s) | |||

2 | 7.890 | 17.806 | 8.467 | 26.272 |

5 | 12.356 | 27.884 | 13.259 | 41.143 |

10 | 14.887 | 33.595 | 15.975 | 49.570 |

20 | 17.566 | 43.607 | 20.735 | 64.342 |

50 | 21.139 | 57.246 | 27.221 | 84.468 |

100 | 23.819 | 67.191 | 31.950 | 99.140 |

200 | 26.498 | 74.750 | 35.544 | 110.294 |

Data | Required Values | Result |
---|---|---|

Zone | D_{90} (mm) (Average) | n_{o} |

La Chimba sub-basin | 0.12 | 0.0266 |

Guanaco sub-basin | 0.14 | 0.0273 |

**Table 9.**Value of the Manning roughness coefficient sub-indices—the Cowan method. In addition, the value of the volume of the debris flow (V

_{d}) is considered with a value of 367,647 m

^{3}and an average velocity (V

_{m}) of 3.03 m/s for the maximum intensity of rainfall in a hydrograph time of 1.5 h.

Required Values | Result | |||||||
---|---|---|---|---|---|---|---|---|

Zone | m | n_{o} | n_{1} | n_{2} | n_{3} | n_{4} | n′ | Total |

La Chimba sub-basin | 1.15 | 0.0266 | 0.005 | 0.005 | 0 | 0.01 | 0.0535 | Floor; fine-coarse gravel, perimeter irregularity; slight, variation sections; occasionally alternate, obstructions; despicable, vegetation; low and sinuosity; appreciable-high |

Guanaco sub-basin | 1.15 | 0.0273 | 0.005 | 0.005 | 0 | 0.01 | 0.0543 | Floor; fine-coarse gravel, perimeter irregularity; slight, variation sections; occasionally alternate, obstructions; despicable, vegetation; low and sinuosity; mild |

Relief Parameters | |||||
---|---|---|---|---|---|

Zone | Maximum and Mínimum Elevation (HM) (Hm) (m a.s.l.) | Absolute Slope (H) (m) | Mean Basin Slope (Pm) (%) | Main Channel Slope (Pcp) (%) | Hypsometric Curve (C_{H}) |

La Chimba basin | 1062–272 | 790 | 30.285 | 16.200 | Young basin |

La Chimba sub-basin | 1062–276 | 786 | 26.744 | 16.200 | Young sub-basin |

Guanaco sub-basin | 988–272 | 716 | 33.825 | 27.558 | Young sub-basin |

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**MDPI and ACS Style**

Roldán, F.; Salazar, I.; González, G.; Roldán, W.; Toro, N.
Flow-Type Landslides Analysis in Arid Zones: Application in La Chimba Basin in Antofagasta, Atacama Desert (Chile). *Water* **2022**, *14*, 2225.
https://doi.org/10.3390/w14142225

**AMA Style**

Roldán F, Salazar I, González G, Roldán W, Toro N.
Flow-Type Landslides Analysis in Arid Zones: Application in La Chimba Basin in Antofagasta, Atacama Desert (Chile). *Water*. 2022; 14(14):2225.
https://doi.org/10.3390/w14142225

**Chicago/Turabian Style**

Roldán, Francisca, Iván Salazar, Gabriel González, Walter Roldán, and Norman Toro.
2022. "Flow-Type Landslides Analysis in Arid Zones: Application in La Chimba Basin in Antofagasta, Atacama Desert (Chile)" *Water* 14, no. 14: 2225.
https://doi.org/10.3390/w14142225