Prediction of total landslide volume in watershed scale under rainfall events using a probability model

Abstract This study established a probability model based on the landslide spatial and size probabilities to predict the possible volume and locations of landslides in watershed scale under rainfall events. First, we assessed the landslide spatial probability using a random forest landslide susceptibility model including intrinsic causative factors and extrinsic rainfall factors. Second, we calculated the landslide volume probability using the Pearson type V distribution. Lastly, these probabilities were joined to predict possible landslide volume and locations in the study area, the Taipei Water Source Domain, under rainfall events. The possible total landslide volume in the watershed changed from 1.7 million cubic meter under the event with 2-year recurrence interval to 18.2 million cubic meter under the event with 20-year recurrence interval. Approximately 62% of the total landslide volume triggered by the rainfall events was concentrated in 20% of the slope units. As the recurrence interval of the events increased, the slope units with large landslide volume tended to concentrate in the midstream of Nanshi River subwatershed. The results indicated the probability model posited can be used not only to predict total landslide volume in watershed scale, but also to determine the possible locations of the slope units with large landslide volume.

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Modelling Daily Surface Runoff, Sediment and Nutrient Loss at Watershed Scale Employing APEX Model Interfaced with GIS – A Case Study in Himalayan Landscape

10.21203/rs.3.rs-232906/v1 ◽

2021 ◽

Author(s):

Suresh Kumar ◽

Ravinder Pal Singh ◽

Justin George Kalambukattu

Keyword(s):

Surface Runoff ◽

Nutrient Loss ◽

Total Carbon ◽

Watershed Scale ◽

Rainfall Events ◽

High Rainfall ◽

Sediment Routing ◽

Sediment Loss ◽

Runoff Sediment ◽

Apex Model

Abstract Daily surface runoff, sediment and nutrient loss data collected from a watershed located in Uttarakhand state of Indian Himalayan region, in year 2010-2011 and of which half of the events data were used for calibration and remaining for validation. Model was calibrated for surface runoff, sediment loss and nutrient loss to optimize the input given to the model to predict the sediment loss, erosion and nutrient loss. The calibration was done by changing the sensitive parameters. Analysis showed that SCS CN number was found most sensitive to runoff, followed by saturated hydraulic conductivity, available water-holding capacity, CN retention parameter and C factor whereas erosion control practice (P) factor was found to be most sensitive, followed by C factor, sediment routing coefficient, average upland slope and soil erodibility (K) factor for the sediment and nutrient loss. APEX model calibrated for the watershed and it predicted quite well for the surface runoff (r=0.92, NSE=0.50), sediment loss (r=0.88, NSE=0.61 and nutrients of total carbon (r=0.78, NSE=0.59) and fairly for total nitrogen (r=0.77, NSE=0.19). Surface runoff was predicted well for low and medium rainfall; however, it was over predicted for high rainfall events. Over prediction may be attributed to the unaccountable conservation measures and practices which were not accounted by the model. Similarly, sediment loss was estimated on daily basis at the watershed scale and was well predicted for low and medium rainfalls but under-estimated for high rainfall events. The area is prone to landslips occurred at high rainfall events was not accounted by the model that may be a reason for under prediction of sediment loss by the model.

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Piecewise prediction model for watershed-scale erosion and sediment yield of individual rainfall events on the Loess Plateau, China

Hydrological Processes ◽

10.1002/hyp.10020 ◽

2013 ◽

Vol 28 (21) ◽

pp. 5322-5336 ◽

Cited By ~ 9

Author(s):

Yu Guo-Qiang ◽

Zhang Mao-Sheng ◽

Li Zhan-Bin ◽

Li Peng ◽

Zhang Xia ◽

...

Keyword(s):

Prediction Model ◽

Loess Plateau ◽

Sediment Yield ◽

Watershed Scale ◽

The Loess Plateau ◽

Rainfall Events

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Long-Term Temporal Variation of Extreme Rainfall Events in Australia: 1910–2006

Journal of Hydrometeorology ◽

10.1175/2010jhm1204.1 ◽

2010 ◽

Vol 11 (4) ◽

pp. 950-965 ◽

Cited By ~ 29

Author(s):

Guobin Fu ◽

Neil R. Viney ◽

Stephen P. Charles ◽

Jianrong Liu

Keyword(s):

Temporal Variation ◽

Extreme Events ◽

Extreme Precipitation ◽

Southern Oscillation ◽

Extreme Rainfall ◽

Temporal Variations ◽

Recurrence Interval ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Extreme Precipitation Events

Abstract The temporal variability of the frequency of short-duration extreme precipitation events in Australia for the period 1910–2006 is examined using the high-quality rainfall dataset identified by the Bureau of Meteorology, Australia, for 189 stations. Extreme events are defined by duration and recurrence interval: 1, 5, 10, and 30 days, and 1, 5, and 20 yr, respectively. The results indicate that temporal variations of the extreme precipitation index (EPI) for various durations and recurrence intervals in the last 100 yr, except for the low frequencies before 1918, have experienced three U-shaped cycles: 1918–53, 1953–74, and 1974–2006. Seasonal results indicate that about two-thirds of 1-day, 1-yr recurrence interval extreme events occur from December to March. Time series of anomalies of the regional EPIs for four regions indicate that northeast Australia and southeast Australia have almost the same temporal variation as the national anomalies, South Australia experienced a negative anomaly of extreme rainfall events in the mid-1950s, and southwest Western Australia (SWWA) experienced relatively small temporal variation. The relationships between extreme rainfall events and the Southern Oscillation index (SOI) and the interdecadal Pacific oscillation (IPO) indicate that extreme rainfall events in Australia have a strong relationship with both, especially during La Niña years and after 1942.

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Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

Natural Hazards and Earth System Science ◽

10.5194/nhess-13-2353-2013 ◽

2013 ◽

Vol 13 (9) ◽

pp. 2353-2367 ◽

Cited By ~ 7

Author(s):

C. Y. Wu ◽

S. C. Chen

Keyword(s):

Probability Model ◽

Landslide Hazard ◽

Landslide Risk ◽

Landslide Area ◽

Related Factors ◽

Frequency Distributions ◽

Annual Probability ◽

Pearson Type ◽

Susceptibility Model ◽

Recurrence Intervals

Abstract. Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.

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Probability Distribution and Characterization of Daily Precipitation Related to Tropical Cyclones over the Korean Peninsula

Water ◽

10.3390/w12041214 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1214

Author(s):

Angelika L. Alcantara ◽

Kuk-Hyun Ahn

Keyword(s):

Tropical Cyclones ◽

Probability Distributions ◽

Maximum Rainfall ◽

Rainfall Events ◽

Gamma Distributions ◽

Pearson Type ◽

Landfalling Tropical Cyclones ◽

Annual Maximum Rainfall ◽

Pearson Type Iii Distribution

Rainfall events are known to be driven by various synoptic disturbances or dominant processes in the atmosphere. In spite of the diverse atmospheric contributions, the assumption of homogeneity is commonly adopted when a hydrological frequency analysis is conducted. This study examines how the dominant processes, particularly the landfalling tropical cyclones (TCs) and non-TC events, have various effects to the characteristics of rainfall in South Korea. With rainfall data from the fifty-nine weather stations spread across the country, the multiple contributions of the TC and non-TC rainfall to the relative amount of rainfall, duration, intensity and maximum rainfall, on a seasonal and monthly scale, are first explored in this study. For the second objective, suitable probability distributions for the TC and non-TC time series are identified potentially for a synthetic analysis. Our results indicate that TCs cause a heterogeneous spatial distribution in the rainfall characteristics over the gauge networks particularly in the southern and eastern coastal areas. Some gauges in these areas attribute a significant portion of their amount and annual maximum rainfall to landfalling TCs. The results also show that the Pearson Type III distribution best represents the non-TC wet-day series, while the TC wet-day series can be represented by various distributions including the Weibull and Gamma distributions. From the analysis, we present how the characteristics of TCs differ from non-TCs with the emphasis on the need to consider their individual effects when conducting synthetic analyses.

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Spatial Distribution and Sustainability Implications of the Canadian Groundwater Resources under Changing Climate

Sustainability ◽

10.3390/su13179778 ◽

2021 ◽

Vol 13 (17) ◽

pp. 9778

Author(s):

Ahmad Zeeshan Bhatti ◽

Aitazaz Ahsan Farooque ◽

Qing Li ◽

Farhat Abbas ◽

Bishnu Acharya

Keyword(s):

Climate Change ◽

Newfoundland And Labrador ◽

Prince Edward Island ◽

Potable Water ◽

Groundwater Resources ◽

Climate Change Impacts ◽

Water Source ◽

National Scale ◽

Rainfall Events ◽

Groundwater Availability

Groundwater availability, utilization, sustainability, and climate change implications were assessed at regional and provincial scales of Canada. It remains an unexplored resource, estimated to be renewing between 380 and 625 km3/year. However, the provinces have initiated developing their quantitative and qualitative databases for their accurate inventory. Sustainable groundwater availability at the national scale was estimated as 19,832 m3/person/year (750 km3/year), with high regional variations ranging from 3949 in the densely populated Prince Edward Island (PEI) province to 87,899 in the thinly populated Newfoundland and Labrador (NFL). It fulfills 82%, 43%, and 14% of water requirements of the rural population, irrigation, and industry, respectively. It is the potable water source for more than 9 million people countrywide (24% of the population), and provinces of Quebec, and Ontario (1.3 million people), and PEI (0.15 million people) particularly depend on it. It is mostly a free or nominally charged commodity, but its utilization was found to be well under sustainable limits (40% of recharge) at the provincial scales, i.e., under 4% for all the provinces except New Brunswick (NB), which also had just 8% extraction of sustainable availability. Nevertheless, localized issues of quantitative depletion and qualitative degradation were found at scattered places, particularly in Ontario and Quebec. Climate change impacts of warming and changing precipitations on groundwater underscored its stability with some temporal shifts in recharge patterns. In general, increased recharge in late winters and springs was observed due to reduced frost and more infiltration, and was somewhat decreasing in summers due to more intense rainfall events.

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Calcium hydroxide influence in autogenous self-healing of cement-based materials in various environmental conditions

Ambiente Construído ◽

10.1590/s1678-86212021000200522 ◽

2021 ◽

Vol 21 (2) ◽

pp. 209-224

Author(s):

Deividi Maurente Gomes da Silva ◽

Vanessa Giaretton Cappellesso ◽

Maurício Germano Lopes Garcia ◽

Angela Borges Masuero ◽

Denise Carpena Coitinho Dal Molin

Keyword(s):

Portland Cement ◽

Calcium Hydroxide ◽

Environmental Conditions ◽

Water Source ◽

The Self ◽

Self Healing ◽

Cement Type ◽

Initial Strength ◽

Cement Based Materials ◽

Type V

Abstract Several factors, such as chemical shrinkage or environmental attack can produce concrete cracks. Calcium hydroxide content from the environment or cement hydration can promote the self-healing phenomenon (SHP). This study evaluates the calcium hydroxide concentration influence on the self-healing phenomenon of cement-based materials. Cracked mortars with different types of cement, such as a filler, pozzolanic, and high initial strength, were exposed to four environmental conditions. Titration was the method proposed to determine the amount of calcium hydroxide content leached in the water, and the cracks closure were analyzed by optical microscopy. CPII F (Portland Cement, type II, compound with limestone) samples showed no trend to Ca(OH)2 leached, and to superficial cracking closure. Regarding CPV (Portland cement, type V, high initial strength cement) samples, their behavior showed the highest Ca(OH)2 content to all environmental exposure, and cracking closure to samples in submerged condition. Thus, a significant influence in the cracks´ closure regarding the presence of Ca2+ leached to the exposure environments, and a water source related to this behavior seems to be a primary factor to improve the SHP.

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A Landslide Probability Model Based on a Long-Term Landslide Inventory and Rainfall Factors

Water ◽

10.3390/w12040937 ◽

2020 ◽

Vol 12 (4) ◽

pp. 937 ◽

Cited By ~ 1

Author(s):

Chun-Yi Wu ◽

Yen-Chu Yeh

Keyword(s):

Large Scale ◽

Probability Model ◽

Threshold Value ◽

Rain Gauge ◽

Landslide Inventory ◽

Exceedance Probability ◽

Probability Models ◽

Rainfall Events ◽

One Year

The prediction and advanced warning of landslide hazards in large-scale areas must deal with a large amount of uncertainty, therefore a growing number of studies are using stochastic models to analyze the probability of landslide occurrences. In this study, we used a modified Thiessen’s polygon method to divide the research area into several rain gauge control areas, and divided the control areas into slope units reflecting the topographic characteristics to enhance the spatial resolution of a landslide probability model. We used a 2000–2015 long-term landslide inventory, daily rainfall, and effective accumulated rainfall to estimate the rainfall threshold that can trigger landslides. We then employed a Poisson probability model and historical rainfall data from 1987 to 2016 to calculate the exceedance probability that rainfall events will exceed the threshold value. We calculated the number of landslides occurring from the events when rainfall exceeds the threshold value in the slope units to estimate the probability that a landslide will occur in this situation. Lastly, we employed the concept of conditional probability by multiplying this probability with the exceedance probability of rainfall events exceeding the threshold value, which yielded the probability that a landslide will occur in each slope unit for one year. The results indicated the slope units with high probability that at least one rainfall event will exceed the threshold value at the same time that one landslide will occur within any one year are largely located in the southwestern part of the Taipei Water Source Domain, and the highest probability is 0.26. These slope units are located in parts of the study area with relatively weak lithology, high elevations, and steep slopes. Compared with probability models based solely on landslide inventories, our proposed landslide probability model, combined with a long-term landslide inventory and rainfall factors, can avoid problems resulting from an incomplete landslide inventory, and can also be used to estimate landslide occurrence probability based on future potential changes in rainfall.

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Short-term microbial release during rain events from on-site sewers and cattle in a surface water source

Journal of Water and Health ◽

10.2166/wh.2013.226 ◽

2013 ◽

Vol 11 (3) ◽

pp. 430-442 ◽

Cited By ~ 5

Author(s):

Johan Åström ◽

Thomas J. R. Pettersson ◽

Georg H. Reischer ◽

Malte Hermansson

Keyword(s):

Genetic Markers ◽

Quantitative Polymerase Chain Reaction ◽

Water Source ◽

Short Term ◽

Parasitic Protozoa ◽

Rainfall Events ◽

Faecal Contamination ◽

Cattle Pasture ◽

Rain Events ◽

Positive Correlations

The protection of drinking water from pathogens such as Cryptosporidium and Giardia requires an understanding of the short-term microbial release from faecal contamination sources in the catchment. Flow-weighted samples were collected during two rainfall events in a stream draining an area with on-site sewers and during two rainfall events in surface runoff from a bovine cattle pasture. Samples were analysed for human (BacH) and ruminant (BacR) Bacteroidales genetic markers through quantitative polymerase chain reaction (qPCR) and for sorbitol-fermenting bifidobacteria through culturing as a complement to traditional faecal indicator bacteria, somatic coliphages and the parasitic protozoa Cryptosporidium spp. and Giardia spp. analysed by standard methods. Significant positive correlations were observed between BacH, Escherichia coli, intestinal enterococci, sulphite-reducing Clostridia, turbidity, conductivity and UV254 in the stream contaminated by on-site sewers. For the cattle pasture, no correlation was found between any of the genetic markers and the other parameters. Although parasitic protozoa were not detected, the analysis for genetic markers provided baseline data on the short-term faecal contamination due to these potential sources of parasites. Background levels of BacH and BacR makers in soil emphasise the need to including soil reference samples in qPCR-based analyses for Bacteroidales genetic markers.

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The diagnosis of metabolic storage disease in skin biopsies (a light-, electronmicroscopic, and analytical study)

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100084119 ◽

1978 ◽

Vol 36 (2) ◽

pp. 648-649

Author(s):

W. Jurecka ◽

W. Gebhart ◽

H. Lassmann

Keyword(s):

Storage Disease ◽

Hunter Syndrome ◽

Histochemical Demonstration ◽

Sweat Glands ◽

Type I ◽

Storage Material ◽

Scheie Syndrome ◽

Storage Products ◽

Skin Biopsies ◽

Type V

Diagnosis of metabolic storage disease can be established by the determination of enzymes or storage material in blood, urine, or several tissues or by clinical parameters. Identification of the accumulated storage products is possible by biochemical analysis of isolated material, by histochemical demonstration in sections, or by ultrastructural demonstration of typical inclusion bodies. In order to determine the significance of such inclusions in human skin biopsies several types of metabolic storage disease were investigated. The following results were obtained.In MPS type I (Pfaundler-Hurler-Syndrome), type II (Hunter-Syndrome), and type V (Ullrich-Scheie-Syndrome) mainly “empty” vacuoles were found in skin fibroblasts, in Schwann cells, keratinocytes and macrophages (Dorfmann and Matalon 1972). In addition, prominent vacuolisation was found in eccrine sweat glands. The storage material could be preserved in part by fixation with cetylpyridiniumchloride and was also present within fibroblasts grown in tissue culture.

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