Comprehensive applicability evaluation of four precipitation products at multiple spatiotemporal scales in Northwest China

Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.

Drivers,Trends,and Patterns of Changing Vegetation-greenness in Nansha Islands,China from 2016 to 2022

Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how they relate to climate change and human activities.To resolve this limitation,we studied changes to the Normalized Difference Vegetation Index(NDVI)vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions.Trends of vegetation greenness were analyzed using Sen's slope and Mann-Kendall test at two spatial scales(pixel and island),and driving factor analyses were performed by time-lagged partial correlation analyses.These were related to impacts from human activities and climatic factors under normal(temperature,precipitation,radiation,and Normalized Difference Built-up Index(NDBI))and extreme conditions(wind speed and latitude of IRs)from 2016 to 2022.Results showed:1)among the 22 IRs,NDVI increased/decreased significantly in 15/4 IRs,respectively.Huayang Reef had the highest NDVI change-rate(0.48%/mon),and Zhongye Island had the lowest(–0.29%/mon).Local spatial patterns were in one of two forms:dotted-form,and degradation in banded-form.2)Under normal conditions,human activities(characterized by NDBI)had higher impacts on vegetation-greenness than other factors.3)Under extreme conditions,wind speed(R^(2)=0.2337,P<0.05)and latitude(R^(2)=0.2769,P<0.05)provided limited explanation for changes from typhoon events.Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations‘Ocean Decade’initiative.

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Improved cat swarm optimization for parameter estimation of mixed additive and multiplicative random error model

To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.

Spatiotemporal Evolution Characteristics of Urban Land Surface Temperature Based on Local Climate Zones in Xi’an Metropolitan,China

Local climate zones(LCZs)are an effective nexus linking internal urban structures to the local climate and have been widely used to study urban thermal environment.However,few studies considered how much the temperature changed due to LCZs transformation and their synergy.This paper quantified the change of urban land surface temperature(LST)in LCZs transformation process by combining the land use transfer matrix with zonal statistics method during 2000–2019 in the Xi’an metropolitan.The results show that,firstly,both LCZs and LST had significant spatiotemporal variations and synchrony.The period when the most LCZs were converted was also the LST rose the fastest,and the spatial growth of the LST coincided with the spatial expansion of the built type LCZs.Secondly,the LST difference between land cover type LCZs and built type LCZs gradually widened.And LST rose more in both built type LCZs transferred in and out.Finally,the Xi’an-Xianyang profile showed that the maximum temperature difference between the peaks and valleys of the LST increased by 4.39℃,indicating that localized high temperature phenomena and fluctuations in the urban thermal environment became more pronounced from 2000 to 2019.

Vertical structure of tidal currents in the Xuliujing Section of Changjiang River Estuary

Three long-term fixed acoustic Doppler current profilers were first used for investigating the vertical structure of tidal currents in Xuliujing Section of Changjiang River Estuary.Moreover,three different periods(spring,summer and fall)were also considered for investigating seasonal variations.The semi-diurnal tides were the most energetic,with along-channel speed of up to 80 cm/s for M_(2)constituent,which dominates at all stations with percent energy up to 65%–75%during seasons.The shape of tidal ellipses of the most energetic semi-diurnal constituent M_(2)showed obvious polarization of the flow paralleling to the riverbank,with the minor semi-axis being generally less than 20%of the major one.The maximum velocity of mean current is appeared in top layers at all the three stations,and the velocity decreased with the depth.The seasonal variations of direction are also observed,which is probably caused by complex local topography since the erosion and deposition in riverbed.Observed vertical variation of four parameters of M_(2)ellipses,agreed well with the optimally fit frictional solutions in top and middle layers.However,there was an obvious difference between frictional model and observed data in the lower water column.Discrepancies are probably on account of stratification,which strengthens in summer and fall due to the freshening influence of the Changjiang River Estuary outflow.

Defining the We-map Reference Frames and Providing Mathematical Expressions for Transformation Relations

We-map is an interactive mobile map that can be easily communicated and applied on personal electronic devices,such as personal computers and mobile phones.Therefore,the study of direction systems and coordinate systems is critical,and exploring reference frames is essential in direction and coordinate systems.Despite its significance,existing research on We-map lacks specific solutions for the exploration of reference frames is indispensable for the establishment of accurate direction and coordinate systems.In this paper,we endeavor to address this gap by elucidating the significance of We-map reference frames,defining them with mathematical constraints,summarizing their nature and characteristics,deriving their transformation relationships and representing them through mathematical formulars and equations.Our work contributes to the fundamental theory of We-map and provides valuable systems and support for the mathematical foundation of We-map,map production,and platform development.Ultimately,this research serves to advance the development of We-map.

Using Path Analysis to Identify the Influence of Climatic Factors on Spring Peak Flow Dominated by Snowmelt in an Alpine Watershed

Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.

Ridge estimation iterative solution of ill-posed mixed additive and multiplicative random error model with equality constraints

The reasonable prior information between the parameters in the adjustment processing can significantly improve the precision of the parameter solution. Based on the principle of equality constraints, we establish the mixed additive and multiplicative random error model with equality constraints and derive the weighted least squares iterative solution of the model. In addition, aiming at the ill-posed problem of the coefficient matrix, we also propose the ridge estimation iterative solution of ill-posed mixed additive and multiplicative random error model with equality constraints based on the principle of ridge estimation method and derive the U-curve method to determine the ridge parameter. The experimental results show that the weighted least squares iterative solution can obtain more reasonable parameter estimation and precision information than existing solutions, verifying the feasibility of applying the equality constraints to the mixed additive and multiplicative random error model. Furthermore, the ridge estimation iterative solution can obtain more accurate parameter estimation and precision information than the weighted least squares iterative solution.

Habitat quality assessment of mining cities based on InVEST model—a case study of Yanshan County,Jiangxi Province

The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientifc basis for the ecological protection and green development of mining cities.Taking Yanshan County as an example of a typical mining city,this article discussed the spatial pattern and evolution characteristics of habitat quality in 2000 and 2018 based on the ArcGIS platform and the InVEST model.The conclusions are as below:from 2000 to 2018,the area of farmland and construction land changed the most in the study area.Among them,the area of farmland decreased by 3.48%,and the area of industrial and mining land and construction land increased by 53.25%.Areas of low,relatively low and high habitat quality expanded,and areas of medium and relatively high habitat quality shrank,which is closely related to the distribution of land use.The areas with high habitat degradation degrees appear around cities,mining areas and watersheds,while the areas with low habitat degradation degrees are mainly distributed in the southern woodland.The distribution of cold and hot spots in the habitat quality distribution of Yanshan County presents a pattern of“hot in the south and cold in the north”.The results are of great signifcance to the precise implementation of ecosystem management decisions in mining cities and the creation of a landscape pattern of“beautiful countrysides,green cities,and green mines”.

Properties of the total least squares estimation

Through theoretical derivation, some properties of the total least squares estimation are found. The total least squares estimation is the linear transformation of the least squares estimation, and the total least squares estimation is unbiased. The condition number of the total least squares estimation is greater than the least squares estimation, so the total least squares estimation is easier to be affected by the data error than the least squares estimation. Then through the further derivation, the relationships of solutions, residuals and unit weight variance estimations between the total least squares and the least squares are given.

A complete solution of an improved universal 3D coordinate similarity transformation model

When linearizing three-dimensional(3 D)coordinate similarity transformation model with large rotations,we usually encounter the ill-posed normal matrix which may aggravate the instability of solutions.To alleviate the problem,a series of conversions are contributed to the 3 D coordinate similarity transformation model in this paper.We deduced a complete solution for the 3 D coordinate similarity transformation at any rotation with the nonlinear adjustment methodology,which involves the errors of the common and the non-common points.Furthermore,as the large condition number of the normal matrix resulted in an intractable form,we introduced the bary-centralization technique and a surrogate process for deterministic element of the normal matrix,and proved its benefit for alleviating the condition number.The experimental results show that our approach can obtain the smaller condition number to stabilize the convergence of the interested parameters.Especially,our approach can be implemented for considering the errors of the common and the non-common points,thus the accuracy of the transformed coordinates improves.

Spatio-temporal Dynamic Simulation of Land use and Ecological Risk in the Yangtze River Delta Urban Agglomeration,China

Rapid urbanization leads to dramatic changes in land use patterns,and the land use/cover change(LUCC)can reflect the spatial impact of urbanization on the ecological environment.Simulating the process of LUCC and predicting the ecological risk future changes can provide supports for urban ecological management.Taking the Yangtze River Delta Urban Agglomeration(YRDUA),China as the study area,four developmental scenarios were set on the basis of the land use data from 2005 to 2015.The temporal land use changes were predicted by the integration of the system dynamic and the future land use simulation(SD-FLUS)model,and the geographically weighted regression(GWR)model was used to identify the spatial heterogeneity and evolution characteristics between ecological risk index(ERI)and socio-economic driving forces.Results showed that:1)From 2005 to 2015,the expansion of construction land(7670.24 km^(2))mainly came from the occupation of cultivated land(7854.22 km2).The Kappa coefficient of the SD-FLUS model was 0.886,indicating that this model could be used to predict the future land use changes in the YRDUA.2)Gross domestic production(GDP)and population density(POP)showed a positive effect on the ERI,and the impact of POP exceeded that of GDP.The ERI showed the characteristics of zonal diffusion and a slight upward trend,and the high ecological risk region increased by 6.09%,with the largest increase.3)Under different developmental scenarios,the land use and ecological risk patterns varied.The construction land is increased by 5.76%,7.41%,5.25%and 6.06%,respectively.And the high ecological risk region accounted for 12.71%,15.06%,11.89%,and 12.94%,correspondingly.In Scenario D,the structure of land use and ecological risk pattern was better compared with other scenarios considering the needs of rapid economic and ecological protection.This study is helpful to understand the spatio-temporal pattern and demand of land use types,grasp the ecological security pattern of large-scale areas,and provide scientific basis for the territory development of urban agglomeration in the future.

Scaled unscented transformation method and adaptive Monte Carlo method used for effects of fault parameters estimation on green function matrix in slip distribution inversion

The elements of Green function matrix are the nonlinear functions of fault parameters estimation, the randomness of fault parameters estimation causes that the slip distribution inversion turns to be the parameter estimation problem of total least squares. Second-order approaching function method, scaled unscented transformation(SUT) method and adaptive Monte Carlo method are designed for biases of displacements in rectangular dislocation model. They are used to analyze effects of the length, width,depth and dip of fault with different variances on the corresponding displacements of unit strike slip dislocation fault, unit dip slip dislocation fault and unit tensile dislocation fault. Results of the simulated fault show that compared with second-order approaching function method and adaptive Monte Carlo method, SUT method has better computational efficiency. The second-order term has dominant effects on nonlinear relationship between displacements and the fault parameter in the rectangular dislocation model. The main biases of displacements are near to fault. The corresponding displacements of unit tensile dislocation are mostly susceptible to fault parameters estimation, followed by the unit dip slip dislocation and unit strike slip dislocation. In addition, the vertical displacement is more sensitive to fault parameters estimation than horizontal displacements.

Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction,i.e.,the reproduction of short-term(several decades)historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area,can extend the length of climatic time series and offset the shortage of observations.This can be used to assess regional climate change over a much longer time scale.Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5)dataset for the period of 1850–2000,the Climatic Research Unit(CRU)dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR)of China during the period of 1961–2011,we calibrated and validated monthly average temperature(MAT)and monthly accumulated precipitation(MAP)in the TMR using the delta,physical scaling(SP)and artificial neural network(ANN)methods.Performance and uncertainty during the calibration(1971–1999)and verification(1961–1970)periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA)method.The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables,different data sources,and/or different methods used.According to traditional performance indices,both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999.However,the results differed from those obtained by the RSPA method.This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree)during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset.Overall,the calibrated and verified MAP had a high degree of uncertainty(negative connection degree)regardless of the dataset or reconstruction method used.Therefore,the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study.The results of this study will be useful for short-term(several decades)regional climate reconstruction and longer-term(100 a or more)assessments of regional climate change.

Sediment settlement rate and consolidation time of flling reclamation in coal mining subsidence land

With the continuous growth of the population and the continuous reduction of cultivated land,China’s food security is greatly threatened.In addition,China’s coal mining has been mainly underground mining,causing land subsidence and damaging existing cultivated land.This efect intensifes the contradiction between the growth of the risk population and the reduction of cultivated land.The reclamation of mining subsidence land with Yellow River sediment is often used as an efective way to improve the recovery rate of cultivated land.Shortening the reclamation time and realizing continuous flling are signifcant issues.The work presented in this paper studied the sediment settlement rate and consolidation time by combining theory,feld flling and reclamation tests and numerical simulations.A feld flling test study was carried out in the lowlands of Jibeiwang Village,Qihe County,Shandong Province,China.By calculating the drainage consolidation time,the consolidation factor of 0.015656 m^(2)/d,and the time factor for sediment consolidation of 0.575 were determined.The sediment consolidation time for this test was 9.18 days.The calculation of sediment deposition rate and consolidation time is of great practical signifcance to guide the Yellow River sediment flling,realize continuous flling,and save reclamation time and cost.

Luminescence chronology and age model application for the upper part of the Chumbur-Kosa loess sequence in the Sea of Azov, Russia

A reliable chronology is essentially critical for correlating loess records with other paleoenvironmental time series, as well as for continuing improvements in the reconstruction of paleoenvironment and paleoclimate changes. It is exactly that the scarcity of chronologies across the Sea of Azov has limited the interpretation of climatic and environmental information in the East European Plain. In view of this, this paper conducted an exploratory study to investigate whether the optically stimulated luminescence(OSL) dating of medium-grained quartz could be used to obtain a set of chronologies and the age models could be used to establish an independent time scale since the Late Pleistocene for the Sea of Azov loess. The results showed that an internally consistent set of optical ages for the Azov loess deposited up to ~76 ka. In addition, the ages developed based on magnetic susceptibility and grain size ages models showed good comparability with independent OSL ages at an acceptable range, suggesting that it might be practicable to establish an independent time scale using age models at the Sea of Azov loess, at least for the uppermost part of the Chumbur-Kosa section. Comparison with the ages based on two age models,the grain size ages using fine-grain fractions may provide a more reliable chronological sequence at the Azov loess since the Late Pleistocene. With the help of absolute ages and climate proxies(magnetic susceptibility and grain size), paleoclimatic change in the Sea of Azov have been traced for the Late Pleistocene.

Using modified Soil Conservation Service curve number method to simulate the role of forest in flood control in the upper reach of the Tingjiang River in China

To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.

Determination of Smoothing Factor for the Inversion of Co-seismic Slip Distribution

For the determination of the smoothing factor (also known as the regularization parameter) in the co-seismic slip distribution inversion, the compromise curve between the model roughness and the data fitting residual is generally used to determine (in order to distinguish the method proposed in this paper, the method is called “L curve” according to its shape). Based on the L-curve, the Eclectic Intersection curve as a new method is proposed to determine the smoothing factor in this paper. The results of the simulated experiment show that the inversion accuracy of the parameters of the seismic slip distribution with the smoothing factor determined by the Eclectic Intersection curve method is better than that of the L curve method. Moreover, the Eclectic Intersection curve method and the L curve method are used to determine the smoothing factor of L’Aquila earthquake and the Taiwan Meinong earthquake slip distribution inversion respectively, and the inversion results are compared and analyzed. The analysis results show that the L’Aquila and the Taiwan Meinong actual earthquake slip distribution results are in the range of other scholars at home and abroad, and compared with the L curve method, the Eclectic Intersection curve method has advantages of high computation efficiency, no need to depend on data fitting degree and more appropriate of smoothing factor and so on.