Uncertainty Analysis of Interpolation Methods in Rainfall Spatial Distribution–A Case of Small Catchment in Lyon

Quantification of spatial and temporal patterns of rainfall is an important step toward developing regional water sewage models, the intensity and spatial distribution of rainfall can affect the magnitude and duration of water sewage. However, this input is subject to uncertainty, mainly as a result of the interpolation method and stochastic error due to the random nature of rainfall. In this study, we analyze some rainfall series from 30 rain gauges located in the Great Lyon area, including annual, month, day and intensity of 6mins, aiming at improving the understanding of the major sources of variation and uncertainty in small scale rainfall in-terpolation in different input series. The main results show the model and the parameter of Kriging should be different for the different rainfall series, even if in the same research area. To the small region with high den-sity of rain gauges (15km2), the Kriging method superiority is not obvious, IDW and the spline interpolation result maybe can be better. The different methods will be suitable for the different research series, and it must be determined by the data series distribution.

THE CHARACTERISTICS OF SPATIAL DISTRIBUTION AND TYPES OF APRIL-SEPTEMBER RAINFALL IN THE PEARL RIVER BASIN

With rainfall data of 51 stations in April - September in the Pearl River basin during 1954 - 2003, we have applied the Principal Component Analysis method to research the spatial distribution characteristics of April - September rainfall. The results reveal the following. In the Pearl River basin, there is different precipitation varying from 600 mm to 1900 mm in April - September and precipitation decreases gradually from southeast to northwest. The standard deviation distribution decreases gradually from east to west on the whole. The rainfall distribution of the Pearl River basin has five main types： Type I： there is flood （drought） in the whole region, Type Ⅱ： there is flood （drought） in the north and drought （flood） in the south, Type IlI： there is flood （drought） in the east and drought （flood） in the west, Type IV： there id flood （drought） in the central part and drought （flood） in the east and west, and Type V： there is flood （drought） in center and drought （flood） in north and south. The types of the flood （drought） in the whole region and flood （drought） in the north and drought （flood） in the south appear much more than the others, being 64% of the total. From the 10-year moving average, it is seen that rainfall between April and September in the Pearl River basin region is mainly dry in 1983 - 1992, and mainly dry in the east and wet in the west in 1967 - 1971 and wet in the east and dryin the west in 1979.

STUDY OF RELATIONSHIP BETWEEN URBANIZATION SPEED AND CHANGE IN SPATIAL DISTRIBUTION OF RAINFALL OVER SHANGHAI

Using daily rainfall data of 11 observatory stations over Shanghai for the period 1960-2007,the spatial differences of rainfall over the Shanghai region during periods with slow and rapid urbanization respectively are investigated based on spatial standard deviation of rainfall and its relative variables.Results show that spatial differences increase with the acceleration of urbanization.Spatial distributions of annual rainfall and rainstorm frequency exhibit distinct urban 'rain-island' features during the rapid period of urbanization(1960-1983) while it is opposite in the case of slow urbanization(1984-2007).Changes in the spatial distribution of annual rainfall trends also take place during different periods.Specifically,the variation of annual rainfall exhibits consistent trends over the Shanghai region in the slow urbanization periods.However,inconsistent spatial distribution of variations has taken place over the central districts and suburbs of Shanghai during the rapid urbanization stage.Since the speeding-up of urbanization,the annual rainfall amount over central districts of Shanghai tends to increase while that in the suburbs shows a decreasing trend.In addition,as far as different seasons are concerned,the speed of urbanization exerts insignificant influences on the spatial distribution of rainfall during winter and spring.On the contrary,the rainfall during summer and autumn(especially summer) is featured with an island effect during the rapid urbanization period.

Spatial Estimation of Rainfall Distribution and Its Classification in Duhok Governorate Using GIS

Rainfall is a significant portion of hydrologic data. Rainfall records, however, are often incomplete due to several factors. In this study, the inverse distance weighting (IDW) method integrated with GIS is used to estimate the rainfall distribution in Duhok Governorate. A total of 25 rain fall stations and rainfall data between 2000 and 2010 were used, where 6 rainfall stations were used for cross-validation. In addition, the relationship between interpolation accuracy and two critical parameters of IDW (Power α value, and a radius of influence) was evaluated. Also, the rainfall distribution of Duhok Governorate was classified. As an output of this study and in most cases, the optimal parameters for IDW in interpolating rainfall data must have a radius of influence up to (15 - 60 km). However, the optimal α values varied between 1 and 5. Based on the results of this study, we concluded that the IDW is an appropriate method of spatial interpolation to predict the probable rainfall data in Duhok Governorate using α = 1 and search radius = 105 km for all the 25 rainfall stations.

Effect of the Zagros Mountains on the Spatial Distribution of Precipitation

In order to examine the effect of the Zagros Mountains on precipitation, first, the annual and Seasonal rainfall indices （rain days frequency, rain amount, daily rainfall intensity, and heavy rains） from 43 stations in 1995 - 2004 between the 30° N to 35° N parallels over the mountain range were analyzed. Second, the effect of the Zagros Mountains was studied through the computation of the spatial correlations between the precipitation parameters and the topographic indices （station site elevation, station mean elevation within a radius of 2.5 km, mean elevation of 9 blocks along each of the eight Cartesian directions, and the elevation differences of these 9 blocks from the station mean elevation）. The results showed that in the cold season the maximal rainfall occurs on the upper range of west slope, while in warm season it spreads over the study area. The correlations between precipitation and elevation indices were positive on the north of the stations and negative on the south of the stations, that is, the higher elevations of the stations to the north force the uplifting of the moist air masses and increase rainfall at the stations, while the lower elevations to their south lead the movement of the moist air masses to the stations. This is due to the fact that these stations or slopes are exposed to the moist air masses coming from the Mediterranean Sea and the Persian Gulf. The heavy rain days and the summer sporadic rain events do not show significant correlations with the topographic indices. The findings indicate that the Zagros Mountains intensify the cold period frontal rains especially over the west slope and block the moist air masses from entering the interior parts of the country. Moreover, these mountains play a secondary role in creating rain days. But they are very important in the production of precipitation in the area. Therefore, their absence will decrease the amount of rainfall to their west and, in return, expand the dry climates of their west and east.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

A GIS-based approach for estimating spatial distribution of seasonal temperature in Zhejiang Province, China

This paper presents a Zhejiang Province southeastern China seasonal temperature model based on GIS techniques. Terrain variables derived from the 1 km resolution DEM are used as predictors of seasonal temperature, using a regression-based approach. Variables used for modelling include: longitude, latitude, elevation, distance from the nearest coast, direction to the nearest coast, slope, aspect, and the ratio of land to sea within given radii. Seasonal temperature data, for the observation period 1971 to 2000, were obtained from 59 meteorological stations. Temperature data from 52 meteorological stations were used to construct the regression model. Data from the other 7 stations were retained for model validation. Seasonal temperature surfaces were constructed using the regression equations, and refined by kriging the residuals from the regression model and subtracting the result from the predicted surface. Latitude, elevation and distance from the sea are found to be the most important predictors of local seasonal temperature. Validation determined that regression plus kriging predicts seasonal temperature with a coefficient of determination (R2), between the estimated and observed values, of 0.757 (autumn) and 0.935 (winter). A simple regression model without kriging yields less accurate results in all seasons except for the autumn temperature.

Analysis of Spatial Distribution Characteristics of Heavy Metals in Cultivated Land of Nehe City

This study aimed at gaining the cultivated land quality and the situation of soil pollution, taking Nehe City in Heilongjiang Province as an example, used ordinary Kriging interpolation of geostatistics, investigated the content and spatial distribution of eight kinds of heavy metal elements（namely Cd, Cr, Pb, Cu, Zn, Ni, Hg and As） in farming land soil, then analyzed the distinction and potential source of these heavy metal elements. The result showed that（1） all these elements had a certain amount of accumulation compared with those in the background of Heilongjiang Province, among which the accumulated levels of Cu and As were the highest.（2） Through statistic analyses, it showed that the spatial autocorrelation degrees of these four elements（namely Cd, Cr, Cu and Zn） were higher.（3） The pollution of Cd and Cu was relatively severe.（4） The spatial distribution features of these eight kinds of heavy metal elements were different, and the soil parent material and the human activity played double roles in the content distribution of heavy metal elements in farming land soil.

Study on Simulating Spatial Distribution and Varying Patterns of Urumqi’s Population

In this paper, an approach to simulate the spatial dis- tribution of urban population is proposed using urban land use and population statistical data through the geographical information systems (GIS). Then, the spatial population distribution of Urumqi as a case is simulated by the approach mentioned above and its varying patterns are analyzed by the raster population surface. As a result, producing raster population surface is more accurate and natural than the traditional choropleth map of population density. Concerning the spatial population distribution of Urumqi, the population density declines from south to north and the population distribution mainly presents "T-type", the population distribution presents multi-centre agglomeration and the population distribu- tion of the districts shows different features. The population den- sity varies significantly with the increase in the distance from central business district (CBD). Finally, it is found in this paper that the development history of districts, terrain and traffic road are main factors that have an influence Urumqi’s population dis- tribution. This paper tries to provide more accurate population data for the plan and management of urban land, traffic and public facilities in order to enrich the researches on urban population distribution.

Simulation of Spatial Distribution of Annual Average Precipitation in Shandong Province

Based on DEM data and conventional data of precipitation at 114 meteorological stations in Shandong Province during 1971 -2010, the statistical model of annual average precipitation in Shandong Province was established using SPSS software; DEM data and raster data of latitude and longitude were substituted into the statistical model, and the spatial distribution of annual average precipitation in Shandong Province based on the statistical model was obtained with the aid of ArcGIS software. Afterwards, the difference between actual value of precipitation at stations used in interpolation and simulated value was interpolated using Kriging interpolation method to obtain residual error of precipitation. Finally, the raster da- ta of annual average precipitation based on the regression model were overlaid with residual error of precipitation to obtain the spatial distribution map of annual average precipitation in Shandong Province. It is verified that the simulation result has high accuracy and can reflect the spatial distri- bution of precipitation in Shandong Province.

Characteristics of Rainfall Erosivity Based on Tropical Rainfall Measuring Mission Data in Tibet, China

Rainfall erosivity in Tibet from 2000 to 2OlO was estimated based on simplified erosion prediction model using daily rainfall data derived from the Tropical Rainfall Measurement Misssion （TRMM） 3B42 rainfall measurement algorithm. Semi- monthly erosive rainfall and rainfall erosivity were validated using weather station data. The spatial distribution of annual rainfall erosivity as well as its seasonal and annual variation in Tibet was also examined. Results showed that TRMM 3B42 data could serve as an alternative data source to estimate rainfall erosivity in the area where only data from sparsely distributed weather stations are available. The spatial distribution of rainfall erosivity in Tibet generally resembles the distribution of multi-year average of annual rainfall. Annual rainfall erosivity in Tibet decreased from the southeast to the northwest. The concentration degree of rainfall erosivity shows an increasing trend from the southeast to the northwest. High rainfall erosivity accompanies low rainfall erosivity concentration degree and vice versa. Rainfall erosivity increased in the middle and western Tibet and decreased in the southeastern Tibet during the 11 years of this study.

Full 2D Hydrodynamic Modelling of Rainfall-induced Flash Floods

Mountain catchments are prone to flash flooding due to heavy rainfall. Enhanced understanding of the generation and evolution processes of flash floods is essential for effective flood risk management. However, traditional distributed hydrological models based on kinematic and diffusion wave approximations ignore certain physical mechanisms of flash floods and thus bear excessive uncertainty. Here a hydrodynamic model is presented for flash floods based on the full two-dimensional shallow water equations incorporating rainfall and infiltration. Laboratory experiments of overland flows were modelled to illustrate the capability of the model. Then the model was applied to resolve two observed flash floods of distinct magnitudes in the Lengkou catchment in Shanxi Province, China. The present model is shown to be able to reproduce the flood flows fairly well compared to the observed data. The spatial distribution of rainfall is shown to be crucial for the modelling of flash floods. Sensitivity analyses of the model parameters reveal that the stage and discharge hydrographs are more sensitive to the Manning roughness and initial water content in the catchment than to the Green-Ampt head. Most notably, as the flash flood augments due to heavier rainfall, the modelling results agree with observed data better, which clearly characterizes the paramount role of rainfall in dictating the floods. From practical perspectives, the proposed model is more appropriate for modelling large flash floods.

Ground-active arthropod responses to rainfall-induced dune microhabitats in a desertified steppe ecosystem,China

Different microhabitats along dune slope were found to affect the distribution of plant performances and soil properties in desertified ecosystems. However, the ground-active arthropod responses to rainfall-induced dune microhabitats were largely unknown in desertified regions. At dune top, midslope and bottom, ground-active arthropods were sampled by the method of pitfall traps in addition to the herbaceous and soil measurements during spring, summer and autumn from 2012 to 2013. Ground-active arthropod had a strong dynamics in time, seasonally and yearly in responses to rainfall-induced dune microhabitats and the variations were significant higher than those of soil and herbaceous properties. The abundance distribution of dominant taxa （i.e. Melolonthidae, Carabidae, Glaphyridae, Tenebrionidae and Formicidae families） among dune microhabitats was similar between seasons within the same year, whereas they differed markedly between two sampling years with varying rainfall patterns. A significant （P〈0.05） difference in total abundance, taxa richness and Shannon index among dune microhabitats was found only in certain season time, particularly in 2013; however, no significant （P〉0.05） differences were found among dune microhabitats when averaged on three sampling seasons within the year of either 2012 or 2013. In all, the taxonomical structure differed considerably from the community structure in ground-active arthropod response to rainfall-induced dune microhabitats. The spatial distribution of taxonomical groups among dune microhabitats was significantly affected by inter-annual rainfall changes, whereas that of community structure was affected by both intra- and inter-annual rainfall changes in desertified ecosystems.

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20 - 30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23 - 24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16 - 18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

Comparing different spatial interpolation methods to predict the distribution of fishes:A case study of Coilia nasus in the Changjiang River Estuary

Spatial-temporal distribution of marine fishes is strongly influenced by environmental factors.To obtain a more continuous distribution of these variables usually measured by stationary sampling designs,spatial interpolation methods(SIMs)is usually used.However,different SIMs may obtain varied estimation values with significant differences,thus affecting the prediction of fish spatial distribution.In this study,different SIMs were used to obtain continuous environmental variables(water depth,water temperature,salinity,dissolved oxygen(DO),p H,chlorophyll a and chemical oxygen demand(COD))in the Changjiang River Estuary(CRE),including inverse distance weighted(IDW)interpolation,ordinary Kriging(OK)(semivariogram model:exponential(OKE),Gaussian(OKG)and spherical(OKS))and radial basis function(RBF)(regularized spline function(RS)and tension spline function(TS)).The accuracy and effect of SIMs were cross-validated,and two-stage generalized additive model(GAM)was used to predict the distribution of Coilia nasus from 2012 to 2014 in CRE.DO and COD were removed before model prediction due to their autocorrelation coefficient based on variance inflation factors analysis.Results showed that the estimated values of environmental variables obtained by the different SIMs differed(i.e.,mean values,range etc.).Cross-validation revealed that the most suitable SIMs of water depth and chlorophyll a was IDW,water temperature and salinity was RS,and p H was OKG.Further,different interpolation results affected the predicted spatial distribution of Coilia nasus in the CRE.The mean values of the predicted abundance were similar,but the differences between and among the maximum value were large.Studies showed that different SIMs can affect estimated values of the environmental variables in the CRE(especially salinity).These variations further suggest that the most applicable SIMs to each variable will also differ.Thus,it is necessary to take these potential impacts into consideration when studying the relationship between the spatial distribution of fishes and environmental changes in the CRE.

Spatiotemporal characteristics of rainfall process in a small mountainous catchment

The spatial distribution and temporal process of rainfall are major problems in small mountainous catchments.This study investigated the spatiotemporal characteristics of rainfalls using data obtained from a dense monitoring network(10 gauges)in a small catchment of 48.6 km2.The rainfall process is determined by empirical relations(rainfall-elevation and rainfall-duration relations)with a random fluctuation.The rainfall-elevation relation of event-scale is R=21.7h+4.6,the rainfall-area relations are suggested as a Gaussian distribution,and the rainfall-duration relation is a power law function.The process was investigated at 1-min resolution and characterized by index including the onset time,duration,and center time of the rainfall peak period.Analysis revealed that the errors were random and followed a normal distribution.Consequently,a method that incorporates the relations of rainfall amount and the stochastic errors is proposed to simulate the rainfall process.Comparing with the monitored data,both the errors of simulated rainfall amount and peak intensity were in the range of[−30%,30%].Additionally,the relations of the simulated and monitored rainfall amount/intensity with the area are both very close.This study marks an attempt to establish a framework for simulation of rainfall at a high temporal resolution(1-min)which is significant to the hydrological hazards forecasting,and realizing the spatial distribution of rainfall within a small catchment.

Quantifying spatial distribution of interrill and rill erosion in a loess at different slopes using structure from motion(SfM)photogrammetry

The spatial distribution of interrill and rill erosion is essential for unravelling soil erosion principles and the application of soil and water conservation practices.To quantify interrill and rill erosion and their spatial development,four 30-min rainfalls at 90 mm h^(-1)intensity were consecutively simulated on runoff plots packed with a loess at six slopes of 10°,15°,20°,25°,30°and 35°.The soil surface was measured using the structure from motion(SfM)photogrammetry upon each simulation run,and the runoff and sediment samples were collected and measured at every 10 min.Rills did not develop until the third simulation run.During the initial two runs,the lower third section was more severely eroded than the upper and middle thirds along the slope direction,yet the interrill erosion was statistically uniform from left to right.Rills tended to emerge by both sidewalls and in the lower portion in the third run.The corresponding rill erosion increased with slope from 10°to 20°and then decreased for the slopes steeper,which was consistent with the slope trend of the sediment yield directly measured.The rills expanded substantially primarily via head retreat and to a lesser extent via sideward erosion after receiving another 30-min rainfall.Rill erosion contributed 69.3%of the total erosion loss,and shifted the critical slope corresponding to the maximum loss from 20°to 25°.These findings demonstrate the significance of rill erosion not only in total soil loss but also in its relation to slope,as well as the effectiveness of SfM photogrammetry in quantifying interrill and rill erosion.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Improvement of displacement error of rainfall and wind field forecast associated with landfalling tropical cyclone AMPHAN

Spatial distribution of rainfall and wind speed forecast errors associated with landfalling tropical cyclones(TC)occur significantly due to incorrect location forecast by numerical models.Two major areas of errors are:(i)over-estimation over the model forecast locations and(ii)underestimation over the observed locations of the TCs.A modification method is proposed for real-time improvement of rainfall and wind field forecasts and demonstrated for the typical TC AMPHAN over the Bay of Bengal in 2020.The proposed method to improve the model forecasts is a relocation method through shifting of model forecast locations of TC to the real-time official forecast locations of India Meteorological Department(IMD).The modification is applied to the forecasts obtained from the operational numerical model,the Global Forecast System(GFS)of IMD.Application of the proposed method shows considerable improvement of both the parameters over both the locations.The rainfall forecast errors due to displacement are found to have improved by 44.1%–69.8%and 72.1%–85.2%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 48 h,72 h,and 96 h.Similarly,the wind speed forecasts have improved by 27.6%–56.0%and 63.7%–84.6%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 60 h,72 h,and 84 h.The results show that the proposed technique has capacity to provide improved spatial distributions of rainfall and wind speed forecasts associated with landfalling TCs and useful guidance to operational forecasters.