I. Overview of the mudslide disaster in the Beishan area of Beijing

(1) Physical, geographic and socio-economic overview

The Beishan area of Beijing, collectively known as the Jundu Mountains, belongs to the Yanshan Mountain Range. The mountains are roughly NEE or NE oriented and consist of broken block mountains. The scope of this mudslide disaster assessment is the northwestern part of Miyun County, the central part of Huairou County and the southeastern part of Yanqing County, including 17 townships, covering an area of about 1,800km2.The elevation of the mountains in the Beishan area is generally 500 to 1,000m above sea level, with individual ones reaching more than 1,000m, such as Hetuo Mountain (1,534m), Yunmeng Mountain (1,414m) and Dawu Tip (1,286m), etc. The landform type is medium-low mountains, and the landform type is medium-low mountains. The geomorphology type belongs to the middle and low mountains, and the transition to the southeast is hilly. The water system in the area includes Chaohe River, Baihe River and Huaihe River, all belonging to the Haihe River system. Both the White River and the Chaohe River originate from the grassland of Damshang. They cut across the Yanshan Mountains, meander down and inject into the Miyun Reservoir. Tributaries of the Chao, Bai and Huai Rivers are developed in the district, which can be categorized into 11 basins, namely, the south bank of the Tang River (referred to as the Tang River Basin), the Baimaguan River, the north bank of the Bai River, the Downer River, the west bank of the Chao River (referred to as the Chao River Basin), the Caixiang River, the Liuli River, the Huaisha River, the Yanshi River and the Sha River Basin.

The region is a warm temperate semi-humid continental climate, the average annual temperature of 8 ~ 10 ℃, the highest monthly average temperature of 25.7 ℃, the coldest -6 ℃, the annual temperature difference of 32 ℃. Due to the difference in topographic elevation, mountain range direction and climate wind direction, resulting in uneven spatial and temporal distribution of precipitation, most of the region's average precipitation over the years in the range of 550-700mm, with a localized area of 700-850mm. precipitation is mostly concentrated in the distribution of the annual June-August (Figure 12-7).

Figure 12-7 Contour map of annual average precipitation in the Beishan area of Beijing

Contour unit/mm

The assessment area is relatively convenient for transportation, with the Shatong Railway passing through from the southeast of the area, and there are the Miyun-Gubei Kou, Miyun-Paibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaibaiba, Huairou-Fengning Liulimiao-Sihai and other major highways. In addition, all township (township) government offices are served by ordinary highways, and the main villages are connected to the township (township) government offices by simple roads or avenues.

Industrial and agricultural production in the district is not very developed and the income level is low. Industries are mainly small township enterprises and processing industries. Agriculture is due to the mountainous areas of thin soil and little land, most of the arable land for the ditch dam land. Its quality is poor and natural disasters such as mudslides, floods and droughts often occur, so the yield is low. At present, a considerable number of villages are not self-sufficient in food and have to rely on the state to supply returned grain.

(2) Mudslide Disaster Overview

This region is characterized by frequent mudslide activities, and is one of the most serious mudslide disasters in China. Its development has a long history, the earliest disaster records for the 1867 mudslides occurred in Huairou County Shaheyu Daohe, Zaoshu forest west ditch, Kibiziyu west ditch. Since then, there were 14 serious mudslide disasters until 1991, with an average of one in nine years; nine of them were group mudslides of a larger scope, with a cycle of about one in 14 years. From the time distribution of disaster activities, before 1959, mudslides on average 15 years a time, group mudslides about 30 years a time. 1959 after the mudslides increased the frequency of outbreaks of activities, on average, about 4.5 years a time, of which in 1977 outside the most serious, and the rest of the group for the outbreak. From the regional distribution of disaster activities, the frequency of mudslide activities in the region's various watersheds are not the same: Baimaguan River, Liuli River, Shahe River, the south bank of the White River, four watersheds of the mudslide is relatively active, the cycle of short- to medium-term (two years to a dozen years), the other watersheds for the medium to long term (more than a decade to fifty years), than the regional mudslide activity is less frequent (Table 12-13).

Table 12-13 Periodicity of mudslide activities in various watersheds

Several mudslides since 1959 have often appeared in clusters due to the control of the location of the center of heavy rainfall and the range of heavy rainfall, which is characterized by a strong mass occurrence. However, several mudslide outbreak areas are not in the same area, and along the north-northeast direction of the continuous migration (Figure 12-8). The scale of the successive mudslide activity is mainly small and medium-sized, and the mass of one time flushed out material is generally 1×104-5×104m3.

The frequent mudslide activity in this region has caused more serious damage to people's lives and property. The main direct damage is to cause casualties, destroyed houses, washed away farmland and woodland, blocking transportation roads, washed away power communication facilities, washed away and buried a variety of water conservancy facilities, etc.; In addition, there are also stopping work and production, crop yield reduction and other indirect losses. The main mudslide disaster events and losses in the region are summarized in Table 12-14.

Figure 12-8 Mudslide Disaster Distribution Map of Beishan Area, Beijing

1-1959 Mudslide Outbreak Area; 2-1969 Mudslide Outbreak Area; 3- 1972 Mudslide Outbreak Area; 4-1976 Mudslide Outbreak Area; 5-1989 Mudslide Outbreak Area; 6-1991 Mudslide Outbreak Area

Table 12-14 Mudslide Disaster Losses Statistics

Continued

Note: According to Wei Jinglian and others, slightly modified.

The risk evaluation of mudslide disaster

(1) The basic methods and steps of risk evaluation

1. Firstly, the correlation factors closely related to mudslide are selected among the many influencing factors; then the raw information and data of the correlation factors are counted separately according to the sub-watersheds, so as to determine the criteria for classifying the level; accordingly, the raw information and data are pre-processed into 1-10%, and converted into 1-10%, and then into 1-10%, and then into 1-10%. Accordingly, the raw information and data were generalized and pre-processed into quantitative data ranging from 1 to 10 to indicate the level of each factor.

2. Using the method of gray correlation analysis to determine the correlation degree of each correlation factor, and accordingly determine the weight value of each correlation factor.

3. The product of the generalized scale of each correlation factor multiplied by its weight value is used to determine the historical and potential disaster intensity of each sub-basin; and then the historical and potential intensity are multiplied by its weight value to get the risk index of each sub-basin.

4. Evaluate the risk of mudflow in each sub-basin based on the risk index of the sub-basin obtained.

(2) Calculation process of the risk index

1. Selection of correlation factors and their data

Based on the formation conditions of mudslides, the region is a torrential rainfall-type mudslides. Their formation is mainly closely related to climatic conditions, topographic and geomorphologic conditions, geological and tectonic conditions, as well as human economic activities and the history of mudslide activities. Since this mudslide evaluation is carried out with a small watershed as the basic unit. Therefore, we selected the factors with obvious regional pattern characteristics, which can represent the historical formation conditions and potential formation conditions of mudslides as the correlation factors; we selected the scale of mudslide activities, the frequency of occurrence and the point density of mudslides as the main correlation factors representing the historical conditions of mudslides; we selected the climatic conditions of the number of days of torrential rainfall greater than 50 mm and the average annual rainfall, the maximum elevation difference of the watershed, the maximum elevation difference of the valley, and the average vertical ratio of the bed of the gully as the main correlation factors. The maximum height difference of the watershed, the maximum height difference of the gully and the average longitudinal drop of the gully bed were selected as the three topographic and geomorphic conditions, the degree of tectonic development and the amount of loose solids storage were selected as the two geologic conditions, and the degree of vegetation was selected as the one of the anthropogenic conditions as the potential factors for the formation of the regional mudslide for the evaluation of the risk.

2. Survey statistics and generalization of correlation factors

The results of the survey statistics of the original data of mudslides in 11 sub-basins in the Beishan area of Beijing are shown in Tables 12-15, in which the scale of mudslides is determined according to the amount of the mass of mudslides flushed out in one mudslide, and the degree of weathering of the rocks, the amount of loose solid material reserves and the degree of tectonic development are the results of regional comparison.

Because the statistics in Table 12-15 have both quantitative data and qualitative descriptions, it is difficult to carry out quantitative calculations, so it is necessary to generalize them for preprocessing before carrying out the gray correlation analysis calculations. According to the mudslide development law and characteristics of this area, and referring to the relevant research results, the grading, generalization and assignment criteria of each major correlation factor of mudslide in this area are derived (Table 12-16). All the correlation factors are divided into four levels, and the original values are replaced by 10, 6, 3 and 1 respectively according to the generalization standard of grading from the high level to the low level; taking into account that the higher the degree of vegetation, the less prone to mudslides, i.e., the degree of vegetation has a negative correlation with the activity of mudslides, the assigned values of the degree of vegetation are replaced by 1, 3, 6 and 10 respectively from the high level to the low level.

3. Calculate the correlation degree and weight of the correlation factor

The influencing factors of mudslide are various, among which there are both known and unknown and ambiguous ones. Therefore, the activity process of mudslide can be regarded as a gray system, and the method of gray correlation analysis can be used to determine the degree of correlation between the factors.

Let x(i, j) be the set of gray correlation factors (i represents the number of samples, i=1,2,3...N; j represents each factor, j=1,2,3...M; and N≥M), where x(i, j) is the comparison sequence (i.e., the dominant factor), the steps of correlation degree calculation are as follows:

( 1) Use the homogenization method to make the original data dimensionless, resulting in the homogenization matrix x1 (i, j).

Theory and Practice of Geological Hazard Disaster Assessment

In the formula: x1 (i,j) - homogenized data;

x (i,j) - original data;

--mean of the jth column (j factors) of the original data.]]

1(i,j)-x(i,j) for difference series calculation. The formula ? (i,j) is the absolute difference between the dominant factor and the correlation factor after comparison.

(3) Calculate the maximum absolute difference and minimum absolute difference.

Theory and Practice of Geological Hazard Disaster Assessment

In the formula: ?max - the maximum absolute difference value among all the difference sequences;

Table 12-15 Statistical table of basic information of mudslide in Beishan area, Beijing

Table 12-16 Grading, generalization and assignment criteria of correlation factor

(4) Calculation of correlation coefficient

Theory and practice of geologic disaster assessment

Eq. - correlation coefficient;

k - empirical coefficient, generally taken as 0.5.

(5) Calculate the degree of correlation

Theory and practice of geologic disaster disaster assessment

Equation: R (j) - - the correlation between the comparison sequence (dominant factor) and each of the other factors;

j - the jth column factor.

According to the above steps, the correlation between the dominant factor and the associated factors was calculated by computer, which in turn determined the degree of closeness of their relationship and the size of the contribution made by each factor to the mudflow (i.e., the weight value of each factor).

Using the generalized data, the scale, frequency and point density of mudslides were selected as the dominant factors, and the other factors as the correlators, and the correlation between the dominant factors and correlators were obtained respectively. From the results of the correlation degree calculation, the order of the correlation degree of the mudslide correlation factors is basically the same relative to the three different dominant factors. The average value is taken to obtain the correlation degree of each potential formation condition. In the same way, the average of the three correlations for each dominant factor is used as the correlation of the dominant factor.

Because the historical and potential conditions of mudslides contribute differently to the risk of mudslides, the historical conditions of mudslides (scale, frequency, and point density) can only indicate the degree of mudslide activity in the past; the development trend of future trends and the degree of attenuation depend on the potential conditions of mudslides. Therefore, we take the historical hazard activity level and potential hazard activity conditions as the determining factors for evaluating the hazard risk of mudslides. Individual correlators among these two influences contribute differently to the mudslide hazard. Using the correlation analysis conducted earlier, the sum of the correlation degree of each correlation factor and the weight value of each correlation factor were obtained for historical conditions and potential conditions respectively (Table 12-17).

In addition, we used the Delphi method to obtain the weights of 0.42 and 0.58 for the degree of historical and potential hazardous activities on the risk of mudslides, respectively.

4. Calculation of mudslide risk index in each basin

The mudslide risk index is an index indicating the degree of danger of mudslide activities, and the higher the index, the greater the risk of mudslide activities. The higher the danger index, the greater the danger of mudslide activity. The danger index is calculated by the following formula:

Theory and Practice of Geological Hazard Disaster Assessment

Where: WZ - mudslide danger index;

LD - historical activity intensity of mudslide;

QD - mudslide activity intensity;

Mudslide danger index is an indicator of the degree of danger of mudslide activities.

QD - the potential activity intensity of mudslide;

R1 - the weight of historical hazard intensity, R1=0.42;

R2 - the Weights of potential hazard intensity, R2=0.58;

M=11;

x(i,j)-generalized data;

R(j)-Weight of each correlation factor;

Other symbols have the same meaning as before.

The potential intensity, historical intensity and hazard index of mudslide in each sub-basin are calculated according to the above formula. The calculation results are shown in Table 12-18.

(C) Evaluation of mudslide hazard risk

From the calculation results of the mudslide hazard index, it can be seen that the degree of hazard of mudslide activities in 11 sub-basins of the Beishan area of Beijing is as follows: Liuli River＞Shahe River＞South Bank of the Baihe River＞North Bank of the Baihe River＞Baimaguancang River＞Caixie River＞Yanqi River＞Waishaxi River＞Chaosha River＞Yanghe>Tang River. Downer River.

In order to more intuitively reflect the degree of danger of mudslide activities, based on the danger index of each sub-basin for grading zoning. *** divided into 4 levels: the high danger (Wz>6) of the Liuli River, the Sha River, the south bank of the Baihe River and the north bank of the Baihe River 4 sub-basins; heavy danger (Wz,5 to 6) of the Baimaguan River and the Vegetable Eating River 2 sub-basins; moderate danger (Wz,4 to 5) of the Yansi River and the Huaisha River 2 sub-basins; light danger (Wz, <4) of the Tang River, the Chaohe River and downstream of the River 3 sub-basins (Table 12-19, Figure 12-9).

Table 12-17 Calculation results of the correlation and weight of the dominant factor and the correlation factor of the mudslide activity in the Beishan area of Beijing

Table 12-18 Calculation results of the generalization of the correlation factor of the mudslide activity in the Beishan area of Beijing and the calculation results of the evaluation of the risk

Table 12-19 Summary table of the distribution of the risk of mudslide in the Beishan area of Beijing

Figure 12-9 Distribution of mudslide hazards in the Beishan area of Beijing

1-Height, >6;2-Severe, 5-6;3-Medium, 4-5;4-Slight, <4;5-Mudslide sub-watershed designation

III. Evaluation of vulnerability to mudslide disaster

(I) Basic methods and steps of vulnerability evaluation

1. Taking sub-watersheds as a unit, investigating and counting socio-economic conditions, fixed assets and land-use types; and converting all the social assets (including the gross value of industrial, agricultural and sideline production, fixed assets and the value of land in three parts) into the value of the year 1992 to obtain the total value of social assets and asset density per unit area for each sub-watershed.

2. Divide the average asset and population density per unit of each sub-watershed by the average asset and population density per unit of the whole evaluation area, and multiply the product of the two to get the index of the susceptibility of the watershed to mudslides.

3. Evaluate the susceptibility of the evaluation area to debris flow based on the susceptibility index of each sub-basin.

(2) Calculation process of susceptibility index

1. Investigate and count the socio-economic conditions, fixed assets and various types of land areas of 11 sub-basins in the Beishan area of Beijing, as well as account for the value of the land and various types of assets; and then add them up to get the total societal assets of each sub-basin (Tables 12-20 and 12-21).

Table 12-20 Statistical results of socio-economic and fixed assets in Beishan area, Beijing

Note: 1 mu = 0.066km2 (the same below).

Table 12-21 Statistical result table of land use type and its value in Beishan area, Beijing

2. Calculation of vulnerability index

Vulnerability index is an index that indicates the ability of disaster area to withstand the damage of mudslide. It is closely related to social assets and population density. The larger the vulnerability index, the higher the degree of sensitivity to mudslide activities, and usually the more serious the damage losses generated by the disaster. The method and steps for calculating the vulnerability index are as follows:

(1) Divide the social assets of each subwatershed by the area of the subwatershed to obtain the average assets per unit of each subwatershed. The total social assets of each sub-watershed are divided by the area of the whole evaluation area to derive the average assets per unit of the whole evaluation area.

(2) Compare (divide) the unit average assets and population density of each sub-watershed with the unit average assets and population density of the whole evaluation area respectively, and then multiply their values to get the vulnerability index of each sub-watershed. That is, it is calculated according to the following formula:

Yi = (Ri/Ro) × (Zi/Zo)

In the formula: Yi - the vulnerability index of each sub-basin;

Ri - the population density of each sub-basin/(person) /km2);

Ro - average population density of the evaluation area / (people/km2);

Zi - average assets per unit of each sub-basin / (million yuan/km2);

Zo - average assets per unit in the evaluation area / (million yuan/km2).

The results of the vulnerability index of each sub-watershed calculated according to the above steps are shown in Table 12-22.

Table 12-22 Results of the evaluation of the vulnerability to mudslides in the Beishan area of Beijing

(III) Evaluation of the vulnerability to mudslides

According to the results of the calculation of the vulnerability index of the mudslides, the vulnerability indices of the eleven sub-watersheds are in the following order: Shahe ＞Chao River＞Waisha River＞Yansi River＞Downer River＞Caixue River＞Baimaguan River＞Tang River＞Luri River＞North bank of Baihe River＞South bank of Baihe River.

Based on the distribution of the vulnerability index of each subwatershed, the vulnerability of the whole evaluation area was divided into four levels: two subwatersheds, the Sha River and the Chao River, with extremely heavy vulnerability (Yi, >1.5); two subwatersheds, the Huaisha River and the Yanshou River, with heavy vulnerability (Yi, 1-1.5); and five subwatersheds, the Li River, the Vegetable River, the Tang River, the Baimaguan River, and the Downer River, with moderate vulnerability (Yi, 0.5-1). Guan River, Tang River, Baima River, and Downer River; and 2 subwatersheds with mild vulnerability (Yi,<0.5), the north bank of the Bai River and the south bank of the Bai River (Table 12-23, Figure 12-10).

Table 12-23 Table of results of grading zoning of mudslide susceptibility in Beishan area, Beijing

(IV) Analysis of hazard degree of mudslide

Hazard degree of mudslide refers to the destructive ability and threat degree of mudslide disaster to human life and property under certain natural and socio-economic conditions. It contains two aspects of the danger and vulnerability of mudslide, which can be expressed by the hazard degree index. Calculated according to the following formula:

WX=Wz-Y

In the formula: WX - hazard degree index;

Wz - hazard index;

Y- - vulnerability index.

Figure 12-10 Mudslide hazard vulnerability distribution map of Beishan area, Beijing

1-Extremely severe, >1.5;2-Severe, 1 to 1.5;3-Moderate, 0.5 to 1;4-Slight, <0.5;5 -Mudslide sub-watershed codes

The hazard index of mudslides in the sub-watersheds in the Beishan area of Beijing was calculated (Table 12-24). The order from high to low is as follows: Sha River＞Chao River＞Waisha River＞Yanqi River＞Luri River＞Caixue River＞Baimaguan River＞South Bank of Bai River＞North Bank of Bai River＞Downer River＞Tang River. According to the hazard index, the mudslide hazards in the region are divided into four levels: only the Sha River basin has a very high hazard level (WX, >10); three basins, the Chao River, the Huaisha River, and the Yanqi River, have a high hazard level (WX,5-19); four basins, the Liuli River, the Caixue River, the Baimaguan River, and the south bank of the Baihe River, have a medium hazard level (WX,3-5); and four basins, the Tang River, the north bank of the Baihe River, and the Tang River, the north bank of the Baihe River, and the Tang River, the north bank of the Baihe River, and the Tang River, have a low hazard level (WX,<3). There are 3 watersheds of Tang River, the north bank of Bai River and downstream river (Figure 12-11).

Table 12-24 Calculation results of mudslide hazard index in Beishan area of Beijing

Figure 12-11 Distribution of mudslide hazard intensity in Beishan area of Beijing

1-Extremely high, >10; 2-High, 5～10; 3-Medium. 3～5;4-Low, <3;5-Mudslide sub-watershed code

Fourth, damage loss evaluation of mudslide disaster

(1) The basic methods and steps of damage loss evaluation

1. The damage loss of mudslide disaster of 11 sub-watersheds was investigated and counted, and converted into the 1992 value to get the sum of damage in each sub-basin.

2. Compare the sum of losses in each sub-basin with social assets, fixed assets and gross industrial and agricultural products respectively, and get the rate of damage and loss of different forms of mudslides. The human mortality rate of each sub-basin was obtained by comparing the number of human deaths in each sub-basin with the total population of the present-day basin.

3. The damage loss rate was multiplied by the personnel mortality rate to obtain the damage loss index for each watershed.

4. Evaluate the damage loss of mudslide in each sub-watershed based on the results of the various calculations mentioned above.

Survey, statistics and calculation results are shown in Tables 12-25 to 12-29.

(2) Evaluation of damage loss of mudslide disaster

The order of damage loss of mudslide in various watersheds in the north mountain area of Beijing, from the highest to the lowest, is as follows: Baimaguan River＞North bank of Baihe River＞Luri River＞Tanghe River＞Niuhe River＞Yansu River＞Caixie River＞Nanbian of Baihe River＞Waishaxia River＞Chaoshe River＞Shahe River. According to the results of mudslide damage loss rate calculation, although the ranking of various damage loss rates obtained by different methods is not the same (Table 12-30), the order of their arrangement is more or less the same, and it is basically the same as the distribution of damage loss index.

Table 12-25 Years of occurrence of mudslides and damage loss statistics in Beijing Beishan area

Table 12-26 Damage loss statistics in mudslide watersheds in Beijing Beishan area

Table 12-27 Socio-economic conditions and mudslide losses in Beijing Beishan area

Table 12-28 Damage loss rate calculation results in mudslides in Beijing Beishan area

Table 12-28 Damage loss rate calculation results in mudslides in Beijing Beishan area

Table 12-28 Damage loss rates in mudslides in Beijing Beishan area

Table 12-29 Calculation results of mudslide damage loss index in Beishan area, Beijing

Table 12-30 Ranking table of different statistical calculation results reflecting the degree of mudslide damage loss

According to the calculation results of the mudslide damage loss index Ps, the order of each sub-watershed from high to low is as follows: Baimaguan River>Baihe North Bank>Luri River>Luxu River>Luxu River>Luxu River>Luxu River>Luxu River. Liuli River＞ Downer River＞ Baihe South Bank＞ Tang River＞ Yanqi River＞ Caixue River＞ Huaishe River＞ Chaohe River＞ Shahe River. It can be divided into 4 levels: 2 subwatersheds, Baimaguan River and Baihe River North Bank, with very high damage and loss (Ps, >1); 3 subwatersheds, Liuli River, Baihe River South Bank, and Downer Cow River, with high damage and loss (Ps, 0.2-1); 4 subwatersheds, Tang River, Vegetable Eating River, Huaisa River, and Yanshe River, with medium damage and loss (Ps,0.02-0.2); 4 subwatersheds, Tang River, Vegetable Eating River, Huaisa River, and Yanqi River, with low damage and loss (Ps, <0.2); and 4 subwatersheds, Chao River, Huaisa River, and Yanqi River. <0.2) were in 2 subwatersheds, the Chao River and the Sha River (Table 12-31 and Figure 12-12).

Table 12-31 Grading table of damage loss index of mudslide in Beishan area, Beijing

Figure 12-12 Distribution of damage intensity of mudslide disaster in Beishan area, Beijing

1-Extremely high, >1; 2-High, 0.2～1; 3-Medium. 0.02～0.2;4-Low, <0.02;5-Mudslide sub-watershed code

V. Evaluation of Mudslide Prevention and Control Project

(I) Current Situation of the Mudslide Prevention and Control Project

Mudslides are widely distributed in the Beishan area of Beijing, and it is difficult to predict the time and place of their occurrence, coupled with the fact that natural conditions are poor and the economic level is low. Poor conditions, low economic level, people's awareness of the potential dangers of mudslides, etc., to date, has not yet established a complete mudslide prevention and control system, some of the existing protective engineering facilities, most of which are built for the prevention and control of flash floods and small-scale water conservancy projects. In addition, the average degree of forest vegetation in this area is only 23%, so it is difficult to inhibit mudslide activities, more difficult to resist mudslide damage, resulting in every mudslide to cause serious losses.

(2) Mudslide prevention and control program and its benefit analysis

Beijing Hydrogeology Engineering Geology Brigade and Beijing Geological Research Institute in 1991-1993 had jointly carried out the Beijing Beishan area mudslide disaster survey and its prevention and control program research work, selected the Beijing Beishan area of Miyun County, Panzipai west ditch (belongs to the Baimaguan River basin) and Huairou County, KeTai ditch (belongs to the north bank of the White River basin) two ditches. Mudslides in two ditches of Miyun County (belonging to Baimaguan River basin) and KeTai ditch of Huairou County (belonging to Baihe River north bank basin) were selected for investigation and planning. According to the formation conditions, environmental background, formation process, type characteristics and its development history and development trend of mudslide, the prevention and control program of mudslide was proposed. Its basic measures are as follows:

Engineering measures: according to certain design standards and calibration standards of construction engineering facilities. That is, to ensure that in the occurrence of mudslide and high sand content flood within the design standards, engineering facilities operate normally, the protection of the object is not jeopardized; but also to ensure that in the occurrence of mudslide and high sand content flood within the calibration standards, the engineering facilities are not destroyed, but also to effectively reduce the disaster damage.

Biological measures: mainly closed forests, in order to nourish water, solid soil and solid slopes, regulating surface runoff, weakening the formation of mudslide hydrodynamic conditions, inhibit mudslide activities. At the same time, the development of dry and fresh fruit economic forests, timber forests and peat forests, in order to prosper the economy.

The implementation of the two measures will effectively prevent and control mudslide disasters. Taking this as the basic basis, the input and output analysis of these measures will be carried out, and the two ditches will be used as an example to extend the evaluation of the mudslide disaster prevention and control project in the whole evaluation area.

1.Analysis of the effect of mudslide prevention and control program in the west ditch of Fanzipai

The standard of the engineering facilities is designed according to the defense against the high precipitation of one in 50 years and the guarantee rate of 2%; and the standard of the calibration is the high precipitation of one in 100 years and the guarantee rate of 1%. The upper reaches of the main ditch (Xiaoxitian) in the sub-watershed of Fanzhixi ditch is a large-scale mudslide gully, and the rest of the tributary ditches are small-scale mudslide ditches, and the prevention and control objects are Xiaoxitian ditch and other secondary and tertiary tributary ditches. The main points of the prevention and control engineering planning are: from upstream to downstream, take engineering measures combining stabilization, blocking, protection and drainage, in order to reduce or eliminate the hazards of mudslides and highly sandy floods on villages, cultivated land and highway facilities in the ditch; and at the same time, carry out biological control to weaken the activity of mudslides fundamentally. Investment Estimate and Expected Benefits: The total investment is 3.6169 million yuan, of which 2.9425 million yuan is invested in engineering measures and 674,400 yuan is invested in biological measures. After the completion of the engineering facilities, the initiation and transportation of loose solids can be basically controlled, thus reducing the frequency of mudslide outbreaks, weakening the scale of mudslides and suppressing mudslide hazards. When the forest ecology of the sub-watershed can be rebuilt, it can both inhibit the mudslide activities and make the engineering facilities work more fully and for a longer period of time; at the same time, due to the development of the dry and fresh fruits economic forests and agriculture, the income can be increased by 2,255,700 to 2,484,900 Yuan per year.

2. Effectiveness analysis of the prevention and control program of mudslide in Ke Tai Gully, Huairou County

The design standard of engineering facilities is designed according to the defense against high precipitation of one in 20 years and the guarantee rate of 5%; the calibration standard is the high precipitation of one in 50 years and the guarantee rate of 2%. The main points of the prevention and control engineering planning are: from upstream to downstream to take a combination of blocking, regulating, storing and discharging engineering measures, as well as biological control, in order to mitigate or eliminate the hazards of mudslides and highly sandy floods to Dongwanzi Village and its downstream.

Investment estimates and expected benefits: a total investment of 3,172,800 yuan, of which 2,516,600 yuan is invested in engineering control and 656,600 yuan is invested in biological control. After the completion of engineering facilities and ecological reconstruction, its disaster prevention benefits and ecological benefits are basically the same as those of Fanzipai Xigou. At the same time, it promotes the development of agriculture, dried and fresh fruits, aquaculture and mining industry, and can increase the income of about 700,000 yuan per year (the income from timber forests is not included in the calculation).

(C) Mudslide prevention and control engineering evaluation

Based on the development trend of the mudslide disaster, without effective prevention and control, the damage loss caused will continue to increase; on the contrary, if measures are taken to prevent and control, the damage loss of the mudslide activity will be reduced.

Assuming that the mudslide prevention and control programs of the above two ditches are both completed by the end of 2000, and their effective service life is 50 years, the input-output ratio values of the above two ditches and valleys are as follows: 225.57 × 50/361.69 ≈ 31 for the western ditch of Fanzipai; and 70 × 50/317.28 ≈ 11 for the ditch of Kotagou.

We assume that the following assumptions for the The level of damage loss (i.e., average annual loss) and cumulative loss for mudslides in the Beishan area of Beijing without and with control measures are predicted, respectively.

S loss = S flat (1+A)αt-(1+B)βt

In the formula: S loss - the level of damage loss in the year of prediction;

S flat - the statistical annual average of 1959-1993 level of damage losses;

A - the average annual growth rate of the national economy;

α - the growth coefficient of damage losses occurring with the growth of the national economy;

B - the - the rate of reduction of the average annual damage loss after the adoption of control engineering measures;

β - the coefficient of the impact of control engineering measures on the disaster damage loss;

t - the year of prediction.

Assumptions: the scale of mudslide intensity and frequency of occurrence in the Beishan area of Beijing remain unchanged; the growth rate of the national economy (A) is 7%; in the absence of preventive and curative measures and with the extent of the disaster remaining as it is now, the coefficient of growth of the damage loss due to the growth of the national economy (α) is 50%; the preventive and curative measures are implemented in accordance with the prevention and curative program and are all completed and put into operation at the end of 2000; the damage loss of the mudslides is reduced at the same time. After operation, the damage loss rate of mudslide will be reduced gradually, and the rate of reduction (B) is 10%; the degree of effective prevention and control of mudslide disaster by preventive and control engineering measures (B) is 80%. According to the above formulas and assumptions as well as the annual average loss of mudslide disaster from 1959 to 1993, the level of damage loss and the predicted cumulative loss of each sub-watershed in different years without prevention and control measures are calculated respectively (Table 12-32 and Table 12-33).

Table 12-32 Predicted levels of damage and cumulative losses of mudslides in the Beishan area of Beijing in the absence of control measures

Table 12-33 Predicted levels of damage and cumulative losses of mudslides in the Beishan area of Beijing in the absence of control measures

From the results of the predicted damages, it is clear that the mudslides will continue to grow in the absence of effective control measures, while keeping the scale of the historical intensity and frequency of the mudslides. Without effective prevention and control, the damage loss will continue to grow, doubling in about 20 years; the cumulative loss will grow even faster, doubling in about 10 years on average. If control engineering measures are taken, the level of debris flow damage will be significantly reduced. If the rate of 10% is gradually reduced, then the basic trend of the loss level by 2030 is close to zero, and the cumulative loss, although still increasing, but the growth rate tends to slow (Figure 12-13).

Figure 12-13 Plot of predicted loss levels and cumulative loss curves for mudslides under different conditions

1-Cumulative loss curve without control; 2-Cumulative loss curve after control; 3-Loss level curve without control; 4 -Loss level curve after control