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Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China

  • Shen Wang , Xiaoli Li , Haofei Tian EMAIL logo , Zhenrong Luan , Jia Wang , Haigang Shi , Jibo Wang , Huicong Wang and Yvdong Wang
Published/Copyright: September 19, 2024
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Open Geosciences
From the journal Open Geosciences Volume 16 Issue 1

Abstract

Debris flow is one of the most common types of geological disasters in China. Owing to the influence of topography, geomorphology, geological conditions, human activity, and rainfall debris flow disasters frequently occur in the mountainous areas of Beijing. The research on debris flow in the Beijing area focuses on rainfall and risk evaluation, material sources, and early warning and prevention of debris flow. However, there are few studies on the development characteristics of single-gully debris flow and the prediction of hazardous areas in the Beijing area. Therefore, we chose the debris flow of Bangou Village in Yanqing District of Beijing as the research object. We analyzed the recharge conditions in the ditch domain and predicted the extent of the hazardous area around the gully, providing suggestions for control measures. The dynamic reserves of the loose deposits in the debris flow gully, currently in the development stage, were estimated as 15.48 × 104 m3, representing four supply sources: artificial deposits, alluvium and diluvium, residual slope deposits, and collapse. The peak flow is 24.49 m3/s for a 10-year rainfall event, 27.64 m3/s for a 20-year rainfall event, 31.79 m3/s for a 50-year rainfall event, and 34.93 m3/s for a 100-year rainfall event. The total amounts of solids washed out by a debris flow from the preceding events are 0.70 × 104 m3, 0.79 × 104 m3, 0.91 × 104 m3, and 1.00 × 104 m3, respectively. The size of the debris flow is small, with a maximum hazardous area of 0.2810 km2. We conclude that a small debris flow outbreak in the Bangou Village gully is possible. We expect that the results of this study will provide basic information and help improve debris flow research in Beijing.

Keywords: basic characteristics of debris flow; formation conditions; sediment sources; velocity of debris flow; peak flow; washed-out solids

Abbreviations

N

Debris flow susceptibility score

1 + φ

Debris flow volumetric weight (t/m3)

φ

Sediment correction factor

V C

Average flow rate of debris flow section (m/s)

m w

Coefficient of resistance outside the riverbed

a

Friction coefficient

R C

Hydraulic radius (m)

I

The debris flows hydraulic slope can generally be replaced by the longitudinal slope

q

Rainstorm intensity (L/s hm2)

Q P

Rainstorm flood peak discharge (m3/s)

Q C

Peak flow of debris flow section (m3/s)

Q

Total amount of primary debris flow (m3)

Q H

Total amount of solids washed out by primary debris flow (m3)

t

Rainfall duration (min)

P

Design reproduction time (year)

Ψ

Stormwater runoff coefficient

F

Water catchment area (hm2)

D C

Plugging factor

K

Experience factor

T

Debris flow from start to finish (s)

γ C

Debris flow volumetric weight (t/m3)

γ w

Water volumetric weight (t/m3)

γ H

Volumetric weight of solid material in a debris flow (t/m3)

S

Hazardous area (km2)

A

Basin area (km2)

W

Volume of sediment (104 m3)

D

Length of main gully (km)

H

Maximum height difference (km)

R

Accumulation angle (°)

L

Maximum stacking length (m)

B

Maximum stacking width (m)

1 Introduction

Debris flow is one of the most common types of geological disasters in China [1]. Debris flows in China mainly occur in the central and southwestern regions, with Sichuan, Yunnan, and southeastern Xizang experiencing the most severe debris flow events. The origin of debris flow disasters in China can be classified into seven categories: gully evolution, slope liquefaction, landslide dam failure, engineering abandonment failure, tailings dam failure, glacial lake dam failure, and pile-up body slip erosion [2]. The debris flow in the Beijing area is of the gully-evolution type of storm-induced debris flow. Owing to the influence of topography, geomorphology, geological conditions, human activity, rainfall, and other factors, debris flow disasters frequently occur in the mountainous areas of Beijing [3].

The capital of China, Beijing, is located at the junction of the Taihang Mountains and Yanshan Mountains, with mountainous areas accounting for ∼62% of the total area. The debris flows in Beijing mostly occur in the Miyun, Huairou, Mentougou, Fangshan, Yanqing, Changping, and Pinggu areas. Previous studies have tended to focus on Miyun [4–13], Huairou [14–23], Mentougou [24–32], and Fangshan [33–42]. There are four aspects to debris flow research in the Beijing area: (1) rainfall [28,33,43–51], (2) debris flow risk evaluation [14,49,52–58], (3) material sources of debris flow [6,7,20,23,38,59–63], and (4) debris flow early warning and prevention [4,5,10,29,36,49,50,54,64,65]. Only a few studies have performed a systematic analysis of the characteristics and risk evaluation of single-gully debris flow [3,59,66,67]. In addition, the number of debris flows in Yanqing District is approximately twice the combined number of debris flows in the Pinggu and Changping districts [64], with relatively high research significance of Yanqing District. Therefore, we selected the Bangou Village debris flow gully, located in Yanqing District, as the object of study and investigated the surface characteristics, formation conditions, recharge conditions of loose accumulation, dynamics characteristics, and hazardous areas of debris flow. We hope to contribute to debris flow research and provide geological information for basic research on debris flow in the Beijing area.

2 Geological setting

Yanqing District is located in northwestern Beijing, with high topography in the northeast and low elevation in the southwest (Figure 1a). There are 65 debris flows in Yanqing District (Figure 1b) as of March 2019. The debris flow gully of Bangou Village is located in the middle of northwest Qianjiadian town, Yanqing District, Beijing, China, and is characterized by a gradual decrease in the terrain from east to west and an approximately “elliptical” plan (Figure 2). The gully is locally upright and has an area of 3.51 km2, a “V”-shaped valley, a length of 3.41 km, and a longitudinal gradient of 167.15‰. Moreover, the slope of the mountain body on the bank is 31°, and the vegetation coverage is 60%. Furthermore, the left bank branch gully is long, while the right bank branch gully is even longer. As a characteristic of a typical valley-type debris flow, once heavy rainfall occurs, the banks, slopes, and loose sediment in the main gully are extremely prone to convergence, thus forming a debris flow.

Figure 1 Yanqing District overview map: (a) topographical map of Yanqing District; (b) distribution of debris flow gullies in Yanqing District.
Figure 1

Yanqing District overview map: (a) topographical map of Yanqing District; (b) distribution of debris flow gullies in Yanqing District.

Figure 2 Geographical location and topography of the Bangou Village debris flow gully.
Figure 2

Geographical location and topography of the Bangou Village debris flow gully.

3 Sediment sources

Loose accumulation in the gullies is an integral part of debris flow activity, and the software used to statistically analyze this activity was ArcGIS 10.8. The loose deposits in the debris flow gully of Bangou Village can be classified as artificial deposits, alluvial and diluvium deposits, residual slope deposits, and collapse deposits (Figure 3). The total volume of alluvial and diluvium deposits amounts to 11.00 × 104 m3, with a sediment volume potentially involved in debris flow activity reaching 3.12 × 104 m3. Similarly, the total volume of residual slope products is estimated to be 10.10 × 104 m3, with a sediment volume potentially involved in debris flow activity measuring up to 2.89 × 104 m3. Additionally, the cumulative volume of artificial deposits reaches approximately 33.19 × 104 m3, while the deposit volume potentially associated with debris flow activity is approximately 9.47 × 104 m3. The combined volumes of collapse, landslide, and slump accumulation are calculated as 0.21 × 104 m3, with only 0.01 × 104 m3 of sediment being potentially involved in debris flow activity. The volume of the accumulation can be estimated using different scales based on the data about the location, stability, footprint, and thickness. The analysis results showed that the total volume of loose deposits in the debris flow gully of Bangou Village is 54.5 × 104 m3 and the volume of loose deposits potentially involved in debris flow activity is 15.48 × 104 m3.

Figure 3 Distribution maps of loose deposits and the prediction of the maximum hazardous area in the Bangou Village debris flow.
Figure 3

Distribution maps of loose deposits and the prediction of the maximum hazardous area in the Bangou Village debris flow.

4 Methods

4.1 Identification of debris flow

In this study, based on the Specification Geological Investigation for Debris Flow Stabilization (DT/T 0220-2006), 15 influence factors were selected, and a scoring method was used to identify debris flow gullies in the gully area where Bangou Village is located by combining the topographic and geomorphological characteristics of Bangou Village (Table 1). The analysis results show that the final score of the gully area where Bangou Village is located is 67 (>41), indicating that the gully area in Bangou Village is in the development stage and there is a possibility of small debris flow.

Table 1

Identification standard of the debris flow gully in Bangou Village

No. Influencing factors Bangou Village debris flow gully Score
1 Collapse, landslides, and severity of soil erosion (natural and artificial) Moderate severity 1
2 Sediment supply length ratio (%) 25 8
3 Active strength of ditch exits debris flow No river shape change, mainstream is not biased 1
4 Longitudinal slope of river ditch (°) 165.5 9
5 Regional structural influence Uplift 7
6 Watershed vegetation coverage (%) 80 1
7 A recent fluctuation in the gully (m) 0.4 8
8 Lithological influence Hard rock with weathering and joints 4
9 Loose sediment reserves (104 m3/km2) 15.48 6
10 Slope of hillside (°) 31 5
11 Cross-section of trench in sand-producing area V-type, U-type 5
12 The average thickness of loose sediment in the sand-producing area (m) 0.5 1
13 Watershed area (km2) 3.51 5
14 Relative elevation of the basin (m) 580 4
15 Degree of blockage Slight 2
Total — — 67

4.2 Volumetric weight of debris flow

In the Specification of Geological Investigation for Debris Flow Stabilization (DZ/T0220-2006) Appendix G.2, based on the relationship between the debris flow susceptibility score (N) and volumetric weight (1 + φ), the volumetric weight of the debris flow can be determined with the corresponding score. The debris flow gully susceptibility score for Bangou Village is 67, and the corresponding debris flow volumetric weight (1 + φ) is 1.426 t/m3.

4.3 Velocity of debris flow

The debris flow velocity is determined empirically or semiempirically, and there is no uniform calculation method. The calculations related to debris flow velocity should be performed based on the fluid properties of the debris flow itself. Therefore, in the study, we used the empirical formula of dilute debris flow in the Beijing area to calculate the debris flow velocity.

(1) V C = m w a R C 2 3 I 1 10 ,

V C is the average flow rate of debris flow section (m/s), and m w is the coefficient of resistance outside the riverbed.

According to the investigation results of the ditch area, the external resistance coefficient of the riverbed of the debris flow ditch in Bangou Village was determined based on the Specification of Geological Investigation for Debris Flow Stabilization.

R C is the hydraulic radius (m), and the average water depth can be substituted. Here, I is the debris flow hydraulic slope can generally be replaced by the longitudinal slope. a is the fully considered friction coefficient (debris flow capacity, specific gravity of stones, stone shape factor, longitudinal slope drop, etc.); average a = 1.55.

The survey results show that the longitudinal slope of the valley of the debris flow gully in Bangou Village is 167.15‰ (I = 167.15‰) and the coefficient of resistance outside the riverbed is 4.0 (m w = 4.0). Based on the abovementioned formula, the average flow velocities of the main channel sections were calculated under four storm frequency conditions: 10-year event, 20-year event, 50-year event, and 100-year event (Table 2).

Table 2

Statistics of debris flow velocity in the Bangou Village debris flow gully

Design frequency of rainstorm P Once in 10 years Once in 20 years Once in 50 years Once in 100 years
Coefficient of resistance outside the riverbed, m w 4.0 4.0 4.0 4.0
Fully considered friction coefficient, a 1.55 1.55 1.55 1.55
Hydraulic radius, R c (m) 0.15 0.3 0.6 1.2
Longitudinal slope, I (‰) 167.15 167.15 167.15 167.15
Average flow rate of debris flow section, V C (m/s) 1.22 1.93 3.06 4.86

4.4 Total amount of solids washed out by debris flow

The rainfall flood method is mainly used in this study to calculate the peak flow of debris flow. According to the Standard of Storm Water Runoff Calculation Urban Storm Drainage System Planning and Design (DB11T 969-2013), the mathematical model method is used to calculate the rainstorm intensity (q), rainstorm flood peak discharge (Q P), peak flow of debris flow section (Q C), total amount of primary debris flow (Q), and total amount of solids washed out by primary debris flow (Q H).

(2) q = 3 , 064 ( 1 + 0.74 × lg P ) ( t + 11.35 ) 0.912 ,

where q is the rainstorm intensity (L/s hm2), t is the rainfall duration (min), and P is the design reproduction time (year); 10, 20, 50, or 100.

Applicable scope: t ≤ 180 min, P = 0.25–100.

(3) Q P = q Ψ F ,

where Q P is the rainstorm flood peak discharge (m3/s), and Ψ is the stormwater runoff coefficient. The mountain runoff coefficient is taken to be 0.3 in areas with developed nodal fissures, and F is the water catchment area (hm2).

(4) Q C = ( 1 + φ ) Q P D C ,

where Q C is the peak flow of the debris flow section (m3/s), φ is the sediment correction factor; φ = 0.426, and Q P is the rainstorm flood peak discharge (m3/s).

D C is the plugging factor. The channel of the debris flow in Bangou Village is relatively straight, with a more or less uniform width of the ditch section. There are fewer steep bumps and chokepoints, and D C is determined to be 2.0 according to the Specification of Geological Investigation for Debris Flow Stabilization (DT/T0220-2006; Table I.1).

Q is the total amount of primary debris flow (m3). The time (T) from the start to the end of the debris flow and peak flow of the debris flow section (Q C) can be used to generalize the process as a pentagon, according to the characteristics of the debris flow, calculated by the following formula (5).

(5) Q = K T Q C ,

where K is the experience factor. K varies with the size of the watershed area (F), with the watershed area ranging from 5 km2 < F < 10 km2; K = 0.113, T is the debris flow from start to finish (s).

Q H is the total amount of solids washed out by primary debris flow (m3), based on the Specification of Geological Investigation for Debris Flow Stabilization (DT/T0220-2006) Appendix I.

(6) Q H = Q ( γ C − γ w ) / ( γ H − γ w ) ,

where Q H is the total amount of solids washed out by primary debris flow (m3), Q is the total amount of primary debris flow (m3), γ C is the debris flow volumetric weight (t/m3), γ w is the water volumetric weight (t/m3), and γ H is the volumetric weight of solid material in a debris flow (t/m3).

The test results show that the loose solid accumulation in the gully is gravel, boulder, and powdery soil; gravel:boulder:powdery soil = 5:3:2, and the weighted average value of each type of soil is γ H = 2.2 t/m3. The related calculation results are shown in Table 3.

Table 3

Related calculation statistics of the total amount of debris flow in Bangou Village

Design frequency of rainstorm P Once in 10 years Once in 20 years Once in 50 years Once in 100 years
Precipitation duration, t/(min) 60 60 60 60
Rainstorm intensity, q/(L/s·hm2) 108.78 122.70 141.11 155.04
Sediment correction factor, Ψ 0.3 0.3 0.3 0.3
Catchment area, F/(hm2) 351 351 351 351
Rainstorm flood peak discharge, Q P/(m3/s) 11.45 12.92 14.86 16.33
1 + φ 1.426 1.426 1.426 1.426
Plugging factor, D C 1.5 1.5 1.5 1.5
Peak flow of debris flow section, Q C/(m3/s) 24.49 27.64 31.79 34.93
Experience factor, K 0.202 0.202 0.202 0.202
Duration of debris flow, T/(s) 3,600 3,600 3,600 3,600
Total amount of primary debris flow, Q/(104 m3) 1.78 2.01 2.31 2.54
Debris flow volumetric weight, γ c/(t/m3) 1.474 1.474 1.474 1.474
Water volumetric weight, γ w/(t/m3) 1.00 1.00 1.00 1.00
Volumetric weight of solid material, γ H/(t/m3) 2.20 2.20 2.20 2.20
Total amount of solids washed out by primary debris flow, Q H/(104 m3) 0.70 0.79 0.91 1.00

According to Table I.1 in specification of geological investigation for debris flow stabilization (DZ/T0220-2006), the debris flow heaviness γ c = 1.474, 1 + φ = 1.426, as determined by Table G.2 in (DZ/T0220-2006).

5 Result

The single-gully debris flow hazardous area includes the debris flow gully domain and threat object range, where the accumulation area is the principal part of the hazard that can become a disaster. In the study, the maximum hazardous area prediction was carried out using the formula of single ditch debris flow accumulation areas from the Specification of Geological Investigation for Debris Flow Stabilization (DZ/T0220-2006), calculated as follows (Table 4):

(7) S = 0.6667 L × B − 0.0833 B 2 / ( 1 − cos R ) ,

where L is the maximum stacking length (m), L = 0.8061 + 0.0015A + 0.000033W, B is the maximum stacking width (m), B = 0.5452 + 0.0034D + 0.000031W, R is the debris flow accumulation angle (°), R = 47.8296 − 1.3085D + 8.8876H, A is the basin area (km2), W is the volume of sediment (104 m3), D is the length of main gully (km), and H is the maximum height difference in the basin (km).

Table 4

Related calculation statistics of the maximum hazardous area of debris flow in Bangou Village

Basin area A/(km2) Volume of sediment W/(104 m3) Length of main gully D/(km) Maximum height difference H/(km)
3.51 15.48 3.41 0.58
Accumulation angle, R/(°) Maximum stacking length, L/(km) Maximum stacking width, B/(km) Hazardous area, S/(km2)
48.52 0.8819 0.5573 0.2810

6 Discussion

Research methods for predicting debris flow in hazardous areas primarily include a numerical simulation [68–72], a mathematical model [73–77], and an expert-based empirical formula method [3,59,66]. (1) The numerical simulation method can be explored as the use of computers to perform experiments. During the repeated simulation of debris flow, every detail of debris flow movement can be displayed. If the data collection is sufficiently large and comprehensive, the numerical simulation method can be infinitely close to the actual situation. However, the high cost of data acquisition makes small projects with insufficient funds only choose other methods. (2) By referring to the characteristics of the same type of debris flow system and the relation among several parameters, the mathematical model is demonstrated as mathematical expressions in an approximate generalized way. The method is based on data to improve the model, which is highly objective and not easily affected by subjective factors. (3) Expert-based empirical formula method is commonly summarized and concluded by experts in the field based on their theoretical and practical experience. This method belongs to the semitheoretical and semiempirical prediction model of debris flow danger area, which is considerably influenced by expert experience and without objectivity.

Moreover, no debris flow has been observed in the history of the Bangou Village debris flow gully; thus, it is impossible to obtain the data required for the establishment of a mathematical model, which does not support the use of mathematical models to predict the danger area. Although a numerical simulation method can be selected for the study of the Bangou Village debris flow gully, the cost of data acquisition is exceedingly high, and the project fund cannot support the rental and purchase of instruments. After comprehensive consideration, the prediction research on the hazardous area of Bangou Village debris flow can only be conducted employing the empirical formula method of experts and field investigation verification.

Furthermore, through the comparative analysis of background factors of debris flow gully, basin area, length of main gully, maximum height difference, volume of sediment, maximum stacking length, maximum stacking width, and accumulation angle can be utilized as a quantitative index to predict the maximum danger area of debris flow. According to the prediction formula of the maximum hazardous area in the Specification of Geological Investigation for Debris Flow Stabilization (DZ/T0220-2006), in combination with the satellite image and field investigation, location, scope, and area of the maximum hazardous area of debris flow are finally determined.

7 Conclusions

  1. The debris flow gully in Bangou Village is a typical valley-type debris flow gully in Yanqing District. The dynamic storage capacity of the loose sediment in the basin is 15.48 × 104 m3, which originates from alluvial and diluvium deposits and residual slope products.

  2. With a small debris flow, the debris flow in Bangou Village is in the development stage, and the largest hazardous area is 0.2810 km2.

  3. Currently, a monitoring and early warning system has been set up in the debris flow gully in Bangou Village, and it is recommended that for the comprehensive management of debris flow, a combination of physical source stabilization and drainage guidance must be adopted.

Acknowledgements

We sincerely appreciate the editors and reviewers for their constructive comments. We also thank Yuan Ying and Du Guoliang who critically read the early draft and helped with the data analyses.

  1. Funding information: The research was supported by scientific research fund program of Yunnan Provincial Department of Education (No. 2024J0078), Yunnan Fundamental Research Projects (No. 202401CF070138), Yunnan Fundamental Research Projects (No. 202401AU070142).

  2. Author contributions: Conceptualization – Wang, S., Luan, Z.R., Tian, H.F.; methodology – Wang, S., Wang, J.B., Wang, J., Tian, H.F.; visualization – Wang, H.C., Li, X.L., Tian, H.F.; writing – original draft preparation, Wang, J., Wang, H.C., Wang, S.; and writing  –  review and editing, Shi, H.G., Wang, S., Wang, Y.D. All authors have read and agreed to the published version of the manuscript.

  3. Conflict of interest: The authors state no conflict of interest.

References

[1] Tang XJ, Chen C, Chen M. Discussion on the research progress of early identification monitoring and early warning of debris flow. J Nat Disasters. 2021;30(1):165–73 (in Chinese with English abstract).Search in Google Scholar

[2] Liu CZ. Genetic types of landslide and debris flow disasters in China. Geol Rev. 2014;60(4):858–68 (in Chinese with English abstract).Search in Google Scholar

[3] Zhang XY, Sun YB, Wang S. Development characteristics and dynamics of debris flow in Chedaogou of Shuiquangou village. Yanqing District, Beijing. Miner Exploration. 2021;12(2):9 (in Chinese with English abstract).Search in Google Scholar

[4] Tu XF. Synthetical control of debris-flow in Fanzipai west gully. Beijing City. Chinese J Geol Hazard Control. 1994;(S1):332–8 (in Chinese with English abstract).Search in Google Scholar

[5] Xie H, Zhong D. An approach on debris flow disaster relief plan of Fanzipaixi gully in the mountain area of Beijing. J Mt Res. 2001;(6):560–4 (in Chinese with English abstract).Search in Google Scholar

[6] Hu FB. Character of deposits in Xibailian watershed and discussing on the presentment of debris flows in Beijing Mountain. China: Beijing Forestry University; 2007 (in Chinese with English abstract).Search in Google Scholar

[7] Lv J, Gao JR, Feng-Bing HU. Characteristics and development of the debris flow fan in Shuangjinshao gully. Beijing. Res Soil Water Conserv. 2010;17(1):140–3 (in Chinese with English abstract).Search in Google Scholar

[8] Cao C, Wang YH, Chen JP. Debris flow risk assessment based on cloud in miyun Beijing. National Engineering Geology Annual Conference; 2015 (in Chinese with English abstract).Search in Google Scholar

[9] Tian SW. Study on rainfall threshold and risk evaluation of debris flow – A case on Dawa gully. China: Jilin University; 2017 (in Chinese with English abstract).Search in Google Scholar

[10] Dong XS. Debris flow characteristics and control engineering design of Longtan valley in Miyun Beijing. China: Beijing Forestry University; 2019 (in Chinese with English abstract).Search in Google Scholar

[11] Feng C. Causes of debris flow in Penghesi and comprehensive control measures for prevention. Beijng. Miner Explor. 2019;11:2728–33 (in Chinese with English abstract).Search in Google Scholar

[12] Hu JL. Geological disasters susceptibility assessment in Miyun District based on AHP–information quantity method. Subgrade Eng. 2020;5:11–7 (in Chinese with English abstract).Search in Google Scholar

[13] Wu JL, Ma C, Wang R. Reconstruction of torrent and debris flow events based on dendrogeomorphology – A case study of Longtangou basin in Miyun District, Beijing. J Nat Disasters. 2021;30(1):8 (in Chinese with English abstract).Search in Google Scholar

[14] Xu XW. Research on the risk assessment of debris flow disaster under the support of geographic information system–taking Huairou County. Beijing as an example. J Chizhou Univ. 1995;1:9–16 (in Chinese with English abstract).Search in Google Scholar

[15] Zhong DL, Xie H, Liu S. Debris flow in Ketai gully. Huaiirou County. Beijing. J Mt Res. 2000;(3):212–6 (in Chinese with English abstract).Search in Google Scholar

[16] Zhang L. Analysis for debris flow disaster insurance risk on fuzzy comprehensive evaluation–take Peking as an example. China: Southwestern University of Finance and Economics; 2011 (in Chinese with English abstract).Search in Google Scholar

[17] Liu JX, Wei MJ, Zhou R. Research of thermoluminescence dating for ancient debris flow materials in Qingshui river basin of Beijing. At Energy Sci Technol. 2012;46(B09):736–40 (in Chinese with English abstract).Search in Google Scholar

[18] Meng QF, Wang XL. Geo–hazard assessment and prediction induced by rainfall in Huairou district of Beijing. Hydrogeol Eng Geol. 2016;43(2):167–70 (in Chinese with English abstract).Search in Google Scholar

[19] Liu CW. Exploration and effectiveness analysis of high–density resistivity method on loose deposits in Sandaogou debris flow ditch. Chin J Geol Hazard Control. 2019;30(3):54–9 (in Chinese with English abstract).Search in Google Scholar

[20] Huang ZY. Application of GPR in debris flow disaster investigation in Huairou mountain area, Beijing. China University of Geosciences (Beijing); 2020 (in Chinese with English abstract).Search in Google Scholar

[21] Xia XH, Liu DC. Study on dynamic parameters of debris flow disaster in Zhanmaoyu, Huairou District. Environ Ecol. 2021;3(6):41–6 (in Chinese with English abstract).Search in Google Scholar

[22] Liao LY, Zeng QL, Yuan GX. Characteristics and mechanism of the rainstorm–induced debris flow on July 16 in Huairou, Beijing. J Eng Geol. 2021;29(3):807–16.Search in Google Scholar

[23] Yan WJ, Yan DN. Characteristics and control measures of debris flow disaster in Yanqi Town Beijing. Environ Ecol. 2021;3(3):65–77 (in Chinese with English abstract).Search in Google Scholar

[24] Zhuo BX. Investigating and assessing flood and geological hazard by remote sensing technology in Mentougou District of Beijing. Chin J Geol Hazard Control. 2001;4:87–91 (in Chinese with English abstract).Search in Google Scholar

[25] Nan Y. Research on critical rainfall of debris flow in Mentougou District, Beijing City. China: Beijing Institute of Geology for Mineral Resources; 2009.Search in Google Scholar

[26] Ran SH. The characteristics of geological disasters in Mentougou of Beijing. Geoscience. 2013;8(3):30–4 (in Chinese with English abstract).Search in Google Scholar

[27] Wang SS, Luo SJ. Discussion on the relationship between debris flow and formation lithology. Geoscience. 2015;10(S1):156–60 (in Chinese with English abstract).Search in Google Scholar

[28] Huang XH. Study on starting mechanism and early warning model of debris flow – A case at damo gully. China: Jilin University; 2016 (in Chinese with English abstract).Search in Google Scholar

[29] Zhu DL. The characteristics and the studies of monitoring early warning on debris flow in Mentougou District in Beijing Area. Beijing, China: China University of Geosciences; 2018 (in Chinese with English abstract).Search in Google Scholar

[30] Sun JL. Study on the distribution of debris flow disaster and critical rainfall in Mentougou District, Beijing. Ground Water. 2018;40(4):146–8 (in Chinese with English abstract).Search in Google Scholar

[31] Gan K. Development characteristics and prevention measures of debris flow in Donghe Dich, Xiangyanggou Village, Zhaitang Town, Mentougou District, Beijing. Geoscience. 2019;14(2):48–53 (in Chinese with English abstract).Search in Google Scholar

[32] Yu X. Discussion on debris flow formation conditions in Hongshuiyu area. Beijing Miner Explor. 2019;10(11):2721–7 (in Chinese with English abstract).Search in Google Scholar

[33] Ding GL, Wang YH, Shen YP. Research on the critical rainfall for single channel in the area of Beijing. Science Press; 2015;23(S1):349–54 (in Chinese with English abstract).Search in Google Scholar

[34] Huang LY, Han JC, Ji W. The characteristics of Chechangbeigou debris flow of Zhoukoudian Fangshan District and its stability evaluation. Urban Geol. 2016;11(2):48–55 (in Chinese with English abstract).Search in Google Scholar

[35] Lu L, Jia SM, Mao J. The idea of debris flow warning scheme based on critical soil moisture in Beijing mountain area. Urban Geol. 2016;11(2):6–9 (in Chinese with English abstract).Search in Google Scholar

[36] Shi MY. Study on debris flow prediction and earlier warning system for Nanjiao catchment, Beijing. Jilin University; 2016 (in Chinese with English abstract).Search in Google Scholar

[37] Ding GL, Wang YH, Yao K. Application of early warning technology to multi–parameter and dynamic monitoring of debris flow–A case study of Nanjiao gully in Fangshan District, Beijing. Urban Geol. 2017;12(1):111–6 (in Chinese with English abstract).Search in Google Scholar

[38] Shen J, Li XX, Li QG. Source characteristics of Fangshan typical debris flow and prevention suggestions. Urban Geol. 2017;12(3):46–9 (in Chinese with English abstract).Search in Google Scholar

[39] Liu JL. Field investigation and research of debris flows trigged flows by an extreme rainstorm on July 21. 2012 in Beijing. Beijing Forestry University; 2017 (in Chinese with English abstract).Search in Google Scholar

[40] Shen J, Li YY, Li QG. The characteristic analysis of debris flow in the Fangshan scenic area. Urban Geol. 2018;13(1):59–63 (in Chinese with English abstract).Search in Google Scholar

[41] He C. Debris flow automatic extraction and evaluation simulation based on GF–2 satellite data. Beijing: China University of Geosciences; 2018 (in Chinese with English abstract).10.1109/IGARSS.2019.8898554Search in Google Scholar

[42] Ma CH, Chen J. Application of geological radar technology to investigations of hazardous debris flow: An example from Nan’an. Fangshan District, Beijing. Geol Prospecting. 2019;55(4):1066–72 (in Chinese with English abstract).Search in Google Scholar

[43] Wu ZH, Chu SL. Basic characteristics of the rainstorm–producing mud–rock flow in Beijing Area. Chin J Atmos Sci. 1992;4:476–81.Search in Google Scholar

[44] Wei JL, Zhao B, Dong GZ. Analysis on the rainfall characteristics and the rainfall forecast in connection with the mudflow in mountainous terrain of Beijing. Beijing Geol. 1995;1:10–7.Search in Google Scholar

[45] Wu ZH. The mud–rock flow disaster and their touch off condition by rainfall in Beijing area. Res Soil Water Conserv. 2001;1:67–72.Search in Google Scholar

[46] Bai LP. The research on critical rainfall for debris flow in the mountainous area of Beijing. J Geol Hazards Environ Preservation. 2006;4:101–4.Search in Google Scholar

[47] Bai LP, Sun JL, Nan Y. Analysis of the critical rainfall thresholds for mudflow in Beijing. China Geol Bull China. 2008;5:674–80.Search in Google Scholar

[48] Wang HZ. A study of the critical rainfall volume for mudflows based on historical data in the mountainous area of Beijing. Urban Geol. 2008;1:18–21.Search in Google Scholar

[49] Ma TJ, Yang C. Rainfall condition of triggering debris flows in Beijing mountain regions. Sci Soil Water Conserv. 2017;15(5):103–10.Search in Google Scholar

[50] Chen WH, Yu B, Liu QW. Characteristics and threshold of rainfall triggering debris flow in Beijing mountainous area. Yangtze River. 2021;52(4):27–33.Search in Google Scholar

[51] Zhai SH, Yu JS, Cheng SZ. Research on early warning of storm debris flow in Beijing mountain area. Yangtze River. 2021;52(3):16–20.Search in Google Scholar

[52] Haopeng H. Researches on debris flow hazards evaluation indexes system and method in Beijing. Beijing: China University of Geosciences; 2007.Search in Google Scholar

[53] Yuan FF. Risk assessment of the debris flow gully at Qiulinpu village of Fangshan Distract in Beijing. Beijing: China University of Geosciences; 2014.Search in Google Scholar

[54] Cao C. Study of flash flood and debris flow disaster prediction and early warning system for Xiqugou catchment, Fangshan District, Beijing. Jilin University; 2017.Search in Google Scholar

[55] Zhang Q. The risk assessment research of typical low frequency debris flow in Beijing mountainous region. Beijing Forestry University; 2016.Search in Google Scholar

[56] Ma B, Wang YH, Ding GL. Assessment on debris flow hazard of Xingyuan Village based on catastrophe theory. Subgrade Eng. 2017;4:226–32.Search in Google Scholar

[57] Wang F. Study on rainfall initiation experiment for debris flow materials and initiation process simulation with PFC. Jilin University; 2018.Search in Google Scholar

[58] Bao JJ. Research on debris flow risk assessment method system based on the west hill in Beijing. Beijing: China University of Geosciences; 2019.Search in Google Scholar

[59] Sun YB, Wang S, Gao LH. Development characteristics of debris flow in Huozi gully Nanwandao Yanqing Region. Beijing Geosci. 2021;35(3):753–62 (in Chinese with English abstract).Search in Google Scholar

[60] Li B, Gao JR, Hu FB. Granularity parameter of debris flow deposit in Wanghugou gully, Beijing City. Sci Soil Water Conserv. 2011;9(4):7–22.Search in Google Scholar

[61] Han SS. Design of debris flow prevention in Huangliangqiao gully, Fengjiayu Town. China: Beijing Forestry University; 2016.Search in Google Scholar

[62] Li XW, Liu CN, Wu B. Application and calculation example of grille dam with pile group type in debris flow reinforcing source. Urban Geol. 2017;12(4):76–82.Search in Google Scholar

[63] Guo Y, Liu XX, Shen J. Formation conditions and source characteristics of Niugao Ditch debris flow in Jinling scenic spot. Urban Geol. 2017;12(3):50–54.Search in Google Scholar

[64] Zhao ZH. Study on forecast method and developmental characteristics of debris flow in Beijing mountainous area. Chin J Geol Hazard Control. 2009;20(3):5–10 (in Chinese with English abstract).Search in Google Scholar

[65] Mao J. Studies of monitoring and early warning on debris flow in the Shahe Basin in Beijing Area. Beijing: China University of Geosciences; 2015.Search in Google Scholar

[66] Li JY, Sun YB, Wang S. Characteristics and development trend prediction of debris flow in the south gully of Shiyao village, Yanqing District, Beijing. Miner Explor. 2021;12(6):1462–71 (in Chinese with English abstract).Search in Google Scholar

[67] Li YB, Zhang ZB, Song ZT. Application of high-density resistivity method and ground penetrating radar in exploration of debris flow disasters in Yanqing District of Beijing. Miner Explor. 2020;11(4):831–6 (in Chinese with English abstract).Search in Google Scholar

[68] Liu Y, Zhang D, Guo D. Debris flow run-out prediction based on the shallow-water flow numerical model – a case study of Xulong Gully. Water. 2023;15(11):2072.10.3390/w15112072Search in Google Scholar

[69] Yin H, Zhou W, Peng Z. Numerical simulation of rainfall-induced debris flow in the Hongchun gully based on the coupling of the LHT model and the Pudasaini model. Nat Hazards. 2023;117(3):2553–72.10.1007/s11069-023-05956-5Search in Google Scholar

[70] Tang Y, Guo Z, Wu L. Assessing debris flow risk at a catchment scale for an economic decision based on the LiDAR DEM and numerical simulation. Front Earth Sci. 2022;10(1):821735.10.3389/feart.2022.821735Search in Google Scholar

[71] Zhou L, Fan XM, Xu Q. Numerical simulation and hazard prediction on movement process characteristics of Baige landslide in Jinsha river. J Eng Geol. 2019;27(6):1395–404.Search in Google Scholar

[72] Wang J, Yang S, Ou G. Debris flow hazard assessment by combining numerical simulation and land utilization. Bull Eng Geol Environ. 2018;77(1):13–27.10.1007/s10064-017-1006-7Search in Google Scholar

[73] Jones RP, Rengers FK, Barnhart KR. Simulating debris flow and levee formation in the 2D shallow flow model D‐Claw: Channelized and unconfined flow. Earth Space Sci. 2023;10(2):e2022EA002590.10.1029/2022EA002590Search in Google Scholar

[74] Mi T, Li LH, Xiong ZM. A data-driven method for predicting debris-flow runout zones by integrating multivariate adaptive regression splines and Akaike information criterion. Bull Eng Geol Environ. 2022;81(6):222.10.1007/s10064-022-02701-3Search in Google Scholar

[75] Cheng H, Huang Y, Zhang W. Physical process-based runout modeling and hazard assessment of catastrophic debris flow using SPH incorporated with ArcGIS: A case study of the Hongchun gully. Catena. 2022;212(1):106052.10.1016/j.catena.2022.106052Search in Google Scholar

[76] Shen P, Zhang L, Chen H. EDDA 2.0: Integrated simulation of debris flow initiation and dynamics considering two initiation mechanisms. Geosci Model Dev. 2018;11(7):2841–56.10.5194/gmd-11-2841-2018Search in Google Scholar

[77] Chen L, Zong SC, Li XL. Simulation of landslide/debris flow runout process in Ailaoshan using Voellmy model. South North Water Transf Water Sci Technol. 2017;15(3):113–9.Search in Google Scholar
Received: 2023-10-30
Revised: 2024-02-01
Accepted: 2024-05-22
Published Online: 2024-09-19

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  4. Evolutionary game analysis of government, businesses, and consumers in high-standard farmland low-carbon construction
  5. On the use of low-frequency passive seismic as a direct hydrocarbon indicator: A case study at Banyubang oil field, Indonesia
  6. Water transportation planning in connection with extreme weather conditions; case study – Port of Novi Sad, Serbia
  7. Zircon U–Pb ages of the Paleozoic volcaniclastic strata in the Junggar Basin, NW China
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  10. Multisource remote sensing image fusion processing in plateau seismic region feature information extraction and application analysis – An example of the Menyuan Ms6.9 earthquake on January 8, 2022
  11. Identification of magnetic mineralogy and paleo-flow direction of the Miocene-quaternary volcanic products in the north of Lake Van, Eastern Turkey
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https://doi.org/10.1515/geo-2022-0655
Keywords for this article
basic characteristics of debris flow; formation conditions; sediment sources; velocity of debris flow; peak flow; washed-out solids
Creative Commons
BY 4.0

Articles in the same Issue

  1. Regular Articles
  2. Theoretical magnetotelluric response of stratiform earth consisting of alternative homogeneous and transitional layers
  3. The research of common drought indexes for the application to the drought monitoring in the region of Jin Sha river
  4. Evolutionary game analysis of government, businesses, and consumers in high-standard farmland low-carbon construction
  5. On the use of low-frequency passive seismic as a direct hydrocarbon indicator: A case study at Banyubang oil field, Indonesia
  6. Water transportation planning in connection with extreme weather conditions; case study – Port of Novi Sad, Serbia
  7. Zircon U–Pb ages of the Paleozoic volcaniclastic strata in the Junggar Basin, NW China
  8. Monitoring of mangrove forests vegetation based on optical versus microwave data: A case study western coast of Saudi Arabia
  9. Microfacies analysis of marine shale: A case study of the shales of the Wufeng–Longmaxi formation in the western Chongqing, Sichuan Basin, China
  10. Multisource remote sensing image fusion processing in plateau seismic region feature information extraction and application analysis – An example of the Menyuan Ms6.9 earthquake on January 8, 2022
  11. Identification of magnetic mineralogy and paleo-flow direction of the Miocene-quaternary volcanic products in the north of Lake Van, Eastern Turkey
  12. Impact of fully rotating steel casing bored pile on adjacent tunnels
  13. Adolescents’ consumption intentions toward leisure tourism in high-risk leisure environments in riverine areas
  14. Petrogenesis of Jurassic granitic rocks in South China Block: Implications for events related to subduction of Paleo-Pacific plate
  15. Differences in urban daytime and night block vitality based on mobile phone signaling data: A case study of Kunming’s urban district
  16. Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan
  17. Integrated geophysical approach for detection and size-geometry characterization of a multiscale karst system in carbonate units, semiarid Brazil
  18. Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region
  19. Deep fault sliding rates for Ka-Ping block of Xinjiang based on repeating earthquakes
  20. Improved deep learning segmentation of outdoor point clouds with different sampling strategies and using intensities
  21. Platform margin belt structure and sedimentation characteristics of Changxing Formation reefs on both sides of the Kaijiang-Liangping trough, eastern Sichuan Basin, China
  22. Enhancing attapulgite and cement-modified loess for effective landfill lining: A study on seepage prevention and Cu/Pb ion adsorption
  23. Flood risk assessment, a case study in an arid environment of Southeast Morocco
  24. Lower limits of physical properties and classification evaluation criteria of the tight reservoir in the Ahe Formation in the Dibei Area of the Kuqa depression
  25. Evaluation of Viaducts’ contribution to road network accessibility in the Yunnan–Guizhou area based on the node deletion method
  26. Permian tectonic switch of the southern Central Asian Orogenic Belt: Constraints from magmatism in the southern Alxa region, NW China
  27. Element geochemical differences in lower Cambrian black shales with hydrothermal sedimentation in the Yangtze block, South China
  28. Three-dimensional finite-memory quasi-Newton inversion of the magnetotelluric based on unstructured grids
  29. Obliquity-paced summer monsoon from the Shilou red clay section on the eastern Chinese Loess Plateau
  30. Classification and logging identification of reservoir space near the upper Ordovician pinch-out line in Tahe Oilfield
  31. Ultra-deep channel sand body target recognition method based on improved deep learning under UAV cluster
  32. New formula to determine flyrock distance on sedimentary rocks with low strength
  33. Assessing the ecological security of tourism in Northeast China
  34. Effective reservoir identification and sweet spot prediction in Chang 8 Member tight oil reservoirs in Huanjiang area, Ordos Basin
  35. Detecting heterogeneity of spatial accessibility to sports facilities for adolescents at fine scale: A case study in Changsha, China
  36. Effects of freeze–thaw cycles on soil nutrients by soft rock and sand remodeling
  37. Vibration prediction with a method based on the absorption property of blast-induced seismic waves: A case study
  38. A new look at the geodynamic development of the Ediacaran–early Cambrian forearc basalts of the Tannuola-Khamsara Island Arc (Central Asia, Russia): Conclusions from geological, geochemical, and Nd-isotope data
  39. Spatio-temporal analysis of the driving factors of urban land use expansion in China: A study of the Yangtze River Delta region
  40. Selection of Euler deconvolution solutions using the enhanced horizontal gradient and stable vertical differentiation
  41. Phase change of the Ordovician hydrocarbon in the Tarim Basin: A case study from the Halahatang–Shunbei area
  42. Using interpretative structure model and analytical network process for optimum site selection of airport locations in Delta Egypt
  43. Geochemistry of magnetite from Fe-skarn deposits along the central Loei Fold Belt, Thailand
  44. Functional typology of settlements in the Srem region, Serbia
  45. Hunger Games Search for the elucidation of gravity anomalies with application to geothermal energy investigations and volcanic activity studies
  46. Addressing incomplete tile phenomena in image tiling: Introducing the grid six-intersection model
  47. Evaluation and control model for resilience of water resource building system based on fuzzy comprehensive evaluation method and its application
  48. MIF and AHP methods for delineation of groundwater potential zones using remote sensing and GIS techniques in Tirunelveli, Tenkasi District, India
  49. New database for the estimation of dynamic coefficient of friction of snow
  50. Measuring urban growth dynamics: A study in Hue city, Vietnam
  51. Comparative models of support-vector machine, multilayer perceptron, and decision tree ‎predication approaches for landslide ‎susceptibility analysis
  52. Experimental study on the influence of clay content on the shear strength of silty soil and mechanism analysis
  53. Geosite assessment as a contribution to the sustainable development of Babušnica, Serbia
  54. Using fuzzy analytical hierarchy process for road transportation services management based on remote sensing and GIS technology
  55. Accumulation mechanism of multi-type unconventional oil and gas reservoirs in Northern China: Taking Hari Sag of the Yin’e Basin as an example
  56. TOC prediction of source rocks based on the convolutional neural network and logging curves – A case study of Pinghu Formation in Xihu Sag
  57. A method for fast detection of wind farms from remote sensing images using deep learning and geospatial analysis
  58. Spatial distribution and driving factors of karst rocky desertification in Southwest China based on GIS and geodetector
  59. Physicochemical and mineralogical composition studies of clays from Share and Tshonga areas, Northern Bida Basin, Nigeria: Implications for Geophagia
  60. Geochemical sedimentary records of eutrophication and environmental change in Chaohu Lake, East China
  61. Research progress of freeze–thaw rock using bibliometric analysis
  62. Mixed irrigation affects the composition and diversity of the soil bacterial community
  63. Examining the swelling potential of cohesive soils with high plasticity according to their index properties using GIS
  64. Geological genesis and identification of high-porosity and low-permeability sandstones in the Cretaceous Bashkirchik Formation, northern Tarim Basin
  65. Usability of PPGIS tools exemplified by geodiscussion – a tool for public participation in shaping public space
  66. Efficient development technology of Upper Paleozoic Lower Shihezi tight sandstone gas reservoir in northeastern Ordos Basin
  67. Assessment of soil resources of agricultural landscapes in Turkestan region of the Republic of Kazakhstan based on agrochemical indexes
  68. Evaluating the impact of DEM interpolation algorithms on relief index for soil resource management
  69. Petrogenetic relationship between plutonic and subvolcanic rocks in the Jurassic Shuikoushan complex, South China
  70. A novel workflow for shale lithology identification – A case study in the Gulong Depression, Songliao Basin, China
  71. Characteristics and main controlling factors of dolomite reservoirs in Fei-3 Member of Feixianguan Formation of Lower Triassic, Puguang area
  72. Impact of high-speed railway network on county-level accessibility and economic linkage in Jiangxi Province, China: A spatio-temporal data analysis
  73. Estimation model of wild fractional vegetation cover based on RGB vegetation index and its application
  74. Lithofacies, petrography, and geochemistry of the Lamphun oceanic plate stratigraphy: As a record of the subduction history of Paleo-Tethys in Chiang Mai-Chiang Rai Suture Zone of Thailand
  75. Structural features and tectonic activity of the Weihe Fault, central China
  76. Application of the wavelet transform and Hilbert–Huang transform in stratigraphic sequence division of Jurassic Shaximiao Formation in Southwest Sichuan Basin
  77. Structural detachment influences the shale gas preservation in the Wufeng-Longmaxi Formation, Northern Guizhou Province
  78. Distribution law of Chang 7 Member tight oil in the western Ordos Basin based on geological, logging and numerical simulation techniques
  79. Evaluation of alteration in the geothermal province west of Cappadocia, Türkiye: Mineralogical, petrographical, geochemical, and remote sensing data
  80. Numerical modeling of site response at large strains with simplified nonlinear models: Application to Lotung seismic array
  81. Quantitative characterization of granite failure intensity under dynamic disturbance from energy standpoint
  82. Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China
  83. Rockfall mapping and susceptibility evaluation based on UAV high-resolution imagery and support vector machine method
  84. Statistical comparison analysis of different real-time kinematic methods for the development of photogrammetric products: CORS-RTK, CORS-RTK + PPK, RTK-DRTK2, and RTK + DRTK2 + GCP
  85. Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia
  86. Petrography and geochemistry of pegmatite and leucogranite of Ntega-Marangara area, Burundi, in relation to rare metal mineralisation
  87. Prediction of formation fracture pressure based on reinforcement learning and XGBoost
  88. Hazard zonation for potential earthquake-induced landslide in the eastern East Kunlun fault zone
  89. Monitoring water infiltration in multiple layers of sandstone coal mining model with cracks using ERT
  90. Study of the patterns of ice lake variation and the factors influencing these changes in the western Nyingchi area
  91. Productive conservation at the landslide prone area under the threat of rapid land cover changes
  92. Sedimentary processes and patterns in deposits corresponding to freshwater lake-facies of hyperpycnal flow – An experimental study based on flume depositional simulations
  93. Study on time-dependent injectability evaluation of mudstone considering the self-healing effect
  94. Detection of objects with diverse geometric shapes in GPR images using deep-learning methods
  95. Behavior of trace metals in sedimentary cores from marine and lacustrine environments in Algeria
  96. Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land
  97. Formation mechanism and oil-bearing properties of gravity flow sand body of Chang 63 sub-member of Yanchang Formation in Huaqing area, Ordos Basin
  98. Diagenesis of marine-continental transitional shale from the Upper Permian Longtan Formation in southern Sichuan Basin, China
  99. Vertical high-velocity structures and seismic activity in western Shandong Rise, China: Case study inspired by double-difference seismic tomography
  100. Spatial coupling relationship between metamorphic core complex and gold deposits: Constraints from geophysical electromagnetics
  101. Disparities in the geospatial allocation of public facilities from the perspective of living circles
  102. Research on spatial correlation structure of war heritage based on field theory. A case study of Jinzhai County, China
  103. Formation mechanisms of Qiaoba-Zhongdu Danxia landforms in southwestern Sichuan Province, China
  104. Magnetic data interpretation: Implication for structure and hydrocarbon potentiality at Delta Wadi Diit, Southeastern Egypt
  105. Deeply buried clastic rock diagenesis evolution mechanism of Dongdaohaizi sag in the center of Junggar fault basin, Northwest China
  106. Application of LS-RAPID to simulate the motion of two contrasting landslides triggered by earthquakes
  107. The new insight of tectonic setting in Sunda–Banda transition zone using tomography seismic. Case study: 7.1 M deep earthquake 29 August 2023
  108. The critical role of c and φ in ensuring stability: A study on rockfill dams
  109. Evidence of late quaternary activity of the Weining-Shuicheng Fault in Guizhou, China
  110. Extreme hydroclimatic events and response of vegetation in the eastern QTP since 10 ka
  111. Spatial–temporal effect of sea–land gradient on landscape pattern and ecological risk in the coastal zone: A case study of Dalian City
  112. Study on the influence mechanism of land use on carbon storage under multiple scenarios: A case study of Wenzhou
  113. A new method for identifying reservoir fluid properties based on well logging data: A case study from PL block of Bohai Bay Basin, North China
  114. Comparison between thermal models across the Middle Magdalena Valley, Eastern Cordillera, and Eastern Llanos basins in Colombia
  115. Mineralogical and elemental analysis of Kazakh coals from three mines: Preliminary insights from mode of occurrence to environmental impacts
  116. Chlorite-induced porosity evolution in multi-source tight sandstone reservoirs: A case study of the Shaximiao Formation in western Sichuan Basin
  117. Predicting stability factors for rotational failures in earth slopes and embankments using artificial intelligence techniques
  118. Origin of Late Cretaceous A-type granitoids in South China: Response to the rollback and retreat of the Paleo-Pacific plate
  119. Modification of dolomitization on reservoir spaces in reef–shoal complex: A case study of Permian Changxing Formation, Sichuan Basin, SW China
  120. Geological characteristics of the Daduhe gold belt, western Sichuan, China: Implications for exploration
  121. Rock physics model for deep coal-bed methane reservoir based on equivalent medium theory: A case study of Carboniferous-Permian in Eastern Ordos Basin
  122. Enhancing the total-field magnetic anomaly using the normalized source strength
  123. Shear wave velocity profiling of Riyadh City, Saudi Arabia, utilizing the multi-channel analysis of surface waves method
  124. Effect of coal facies on pore structure heterogeneity of coal measures: Quantitative characterization and comparative study
  125. Inversion method of organic matter content of different types of soils in black soil area based on hyperspectral indices
  126. Detection of seepage zones in artificial levees: A case study at the Körös River, Hungary
  127. Tight sandstone fluid detection technology based on multi-wave seismic data
  128. Characteristics and control techniques of soft rock tunnel lining cracks in high geo-stress environments: Case study of Wushaoling tunnel group
  129. Influence of pore structure characteristics on the Permian Shan-1 reservoir in Longdong, Southwest Ordos Basin, China
  130. Study on sedimentary model of Shanxi Formation – Lower Shihezi Formation in Da 17 well area of Daniudi gas field, Ordos Basin
  131. Multi-scenario territorial spatial simulation and dynamic changes: A case study of Jilin Province in China from 1985 to 2030
  132. Review Articles
  133. Major ascidian species with negative impacts on bivalve aquaculture: Current knowledge and future research aims
  134. Prediction and assessment of meteorological drought in southwest China using long short-term memory model
  135. Communication
  136. Essential questions in earth and geosciences according to large language models
  137. Erratum
  138. Erratum to “Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan”
  139. Special Issue: Natural Resources and Environmental Risks: Towards a Sustainable Future - Part I
  140. Spatial-temporal and trend analysis of traffic accidents in AP Vojvodina (North Serbia)
  141. Exploring environmental awareness, knowledge, and safety: A comparative study among students in Montenegro and North Macedonia
  142. Determinants influencing tourists’ willingness to visit Türkiye – Impact of earthquake hazards on Serbian visitors’ preferences
  143. Application of remote sensing in monitoring land degradation: A case study of Stanari municipality (Bosnia and Herzegovina)
  144. Optimizing agricultural land use: A GIS-based assessment of suitability in the Sana River Basin, Bosnia and Herzegovina
  145. Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index
  146. Analysis of the intensity of erosive processes and state of vegetation cover in the zone of influence of the Kolubara Mining Basin
  147. GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)
  148. Geospatial modeling of wildfire susceptibility on a national scale in Montenegro: A comparative evaluation of F-AHP and FR methodologies
  149. Geosite assessment as the first step for the development of canyoning activities in North Montenegro
  150. Urban geoheritage and degradation risk assessment of the Sokograd fortress (Sokobanja, Eastern Serbia)
  151. Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia
  152. Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities
  153. Forest soil CO2 emission in Quercus robur level II monitoring site
  154. Characterization of glomalin proteins in soil: A potential indicator of erosion intensity
  155. Power of Terroir: Case study of Grašac at the Fruška Gora wine region (North Serbia)
  156. Special Issue: Geospatial and Environmental Dynamics - Part I
  157. Qualitative insights into cultural heritage protection in Serbia: Addressing legal and institutional gaps for disaster risk resilience
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