Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

洪水预报模型输入与输出的误差分布及相关性分析

降雨预报信息作为洪水预报模型的输入,该信息的准确性直接影响洪水预报模型输出的准确性.为探究模型输入(降雨预报)误差与输出(洪水预报)误差之间的关系,以英那河流域为例,分析了不同雨量等级下,预报模型的输入误差与输出误差的分布规律,并定性分析了两种误差的相关关系.结果表明,降雨量等级若为无雨及小雨时,两种误差不相关;若为中...     

CondMerg: an open source implementation in R language of conditional merging for weather radars and rain gauges observations

Monitoring of extreme events requires accurate measurement of rainfall intensities and merging weather radar data with ground information is a very common technique used to obtain the required precision. In order to do this, several methods exist but very few open source implementations are available. CondMerg is the first open source software developed in R language implementing the conditional merging method and some other experimental variants based on it. It is a cross-platform software, easily adaptable to different needs, optimized for batch processing of multiple events but also usable in near real time applications. For its execution it requires two inputs: a CSV file with rain gauges measurements and a geo-referred TIF file with weather radar quantitative precipitation estimations; main outputs are TIF files with merged observations although the code also returns information about cross-validation, with scatter plots and indexes. All TIF files are ready to be managed by common GIS software for easy visualization and analysis. Use of the program is very simple: execution can be interactive or non-interactive and, in both cases, it just requires to set some parameters at the beginning of the program and run it. The code has been tested on different extreme rain events occurred in the Piedmont region (northwestern Italy) showing improved accuracy of reconstructed rainfall fields.     

降水空间不均匀性对径流过程模拟的影响

应用数字高程流域水系模型，通过子流域和网格2种空间离散方式，采用传统的子流域法、雨量插值子流域法、逐个网格法3种雨量数据输入处理方法，分别作日流量模拟与洪水过程模拟，模拟过程与实测水文过程相比较表明：日模中3种雨量处理方法计算精度相当，次模中逐个网格法优于传统子流域法和雨量插值子流域法；降雨空间分布不均匀性考虑得越充分，水文过程模拟精度越高。     

Forecasting Daily Seepage Discharge of an Earth Dam Using Wavelet–Mutual Information–Gaussian Process Regression Approaches

Because of their sensitive structure, earth dams might face failure due to seepage phenomenon. In order to prevent such failure, some equipment like piezometers are installed in the body or foundation of earth dams. This study investigated the importance of piezometer installation level in dam body or foundation using mutual information–wavelet–Gaussian process regression. 27 Piezometers in three section along with reservoir level were employed to predict one-step-ahead seepage discharge of Zonouz earth dam. The daily data of 1 year of piezometer level and reservoir level were collected for this purpose. In order to find the best possible input combination, three groups of modeling scenarios were defined using piezometers and reservoir level time series. As some input combinations had more than two variables, decomposed time series were imposed into mutual information (MI) tool in order to decrement input variables and find the most correlated input–output features. Afterward, mentioned features were imposed into optimized Gaussian process regression (GPR) to be predicted. Different kernels were selected as core tool of GPR, but results demonstrated the capability of radial basis function (RBF) kernel. GPR–RBF structure were optimized using cross-validation technique. Results indicated that input combination including piezometer level and reservoir level of section II, especially piezometer 203 time series led to the best result among all scenarios.     

Analytical solutions of one-dimensional advection-diffusion equation with variable coefficients in a finite domain

Analytical solutions are obtained for one-dimensional advection-diffusion equation with variable coefficients in a longitudinal finite initially solute free domain, for two dispersion problems. In the first one, temporally dependent solute dispersion along uniform flow in homogeneous domain is studied. In the second problem the velocity is considered spatially dependent due to the inhomogeneity of the domain and the dispersion is considered proportional to the square of the velocity. The velocity is linearly interpolated to represent small increase in it along the finite domain. This analytical solution is compared with the numerical solution in case the dispersion is proportional to the same linearly interpolated velocity. The input condition is considered continuous of uniform and of increasing nature both. The analytical solutions are obtained by using Laplace transformation technique. In that process new independent space and time variables have been introduced. The effects of the dependency of dispersion with time and the inhomogeneity of the domain on the solute transport are studied separately with the help of graphs.     

Trend and spatial distribution of rainfall & rainy days over Andaman & Nicobar Islands

The present study examines the characteristics and climatological features of daily rainfall data over Andaman & Nicobar Islands. Analysis of rainfall data reveals a large monthly deviation over the northern latitudes as compare to southern latitudes of Andaman & Nicobar Islands. Also, it is found that rainfall increases from north to south latitudes in all the seasons except monsoon, where a reverse pattern exists. In trend analysis, a statistically significant decreasing trend (confidence level >95?%) is observed for yearly rainfall and rainy days over the region. Analysis of daily rainfall intensity for each year shows increasing trend for frequency of rather heavy rain (35.6?C64.4?mm) and significant decreasing trend for frequencies of light rain (2.5?C7.5?mm), and very heavy rain (>124.5?mm) over the region. Many times, very heavy rain events are associated with cyclonic disturbances affecting Andaman & Nicobar Islands region. The analysis of cyclonic disturbances over the region reveals a stronger and more significant decreasing trend. So, one of the causes for decreasing trend in very heavy rain over Andaman & Nicobar Islands may be due to significant decreasing frequency of cyclonic disturbances affecting this region.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.     

新疆岩石圈三明治结构与油气资源

重力勘探是普查油气盆地常用的方法。利用重力研究岩石圈构造时，卫星重力具有独特的作用。它不但与自由空气重力异常相似。能直接反应岩石圈物质的积聚或亏损。可以获得较深处物质产生的重力场，还可以利用对重力场的分解处理，突出分层深度的异常特征，用以分析研究不同深度物质对重力场的贡献。根据对卫星重力异常的解释，可以将新疆地区岩石圈分成3层。最上层是中新生代陆相断陷盆地巨层。它的特点主要是四盆（伊宁盆地、准噶尔盆地、吐哈盆地和塔里木盆地）三山（阿尔泰山、天山和阿尔金山）的特殊景观。中间层是海相古生代盆山构造巨层。它是在印支-燕山期．强烈的挤压褶皱使地壳发生规律的平行线状排列盆山构造。最下层是低密度块体基底层。新疆地区岩石圈三明治构造的形成是因为在喜马拉雅期．印度板块自西南向东北的俯冲作用下．对古生代末已拼合成大陆的新疆地区进行改造，西天山的婆罗科努山、察布查尔山、阿拉沟山、额尔宾山、霍拉山等山系横向隆升。它们和南天山山脉一起。将新疆地区分割而成。从这项研究中得到启示，西部寻找油气资源不应局限于新生代盆地，而要考虑深部构造对地表出露盆山构造的控制。     

Impact of Higher Frequency Content of Input Motion Upon Equivalent Linear Site Response Analysis for the Study Area of Delhi

While travelling through the subsoil layers, earthquake generated bedrock motions get modified significantly due to local soil and should be quantified using ground response analysis. Present study concentrates on equivalent linear method of site response analysis in SHAKE2000 software. It is a frequency based analysis tool having default frequency set to 15 Hz. While due consideration is given to amplitude, no to very limited information about the frequency content of the input motion to be considered in ground response analysis is available. In the present work, the effect of the maximum frequency of ground motion in site response analysis using SHAKE2000 is examined. Two sets of analyses are carried out in this work based on 30 globally recorded input motions. In the first analyses, input motion up to 15 Hz maximum frequency, which is a default value in SHAKE2000 is considered while second analyses are based on considering each of the 30 input motions up to the Nyquist frequency. Comparing the results from the two sets of analyses highlight that selection of maximum frequency in SHAKE2000 has considerable effect in ground motion amplification at different depths. As a result, even the peak ground acceleration which controls the building behavior and damage scenario, is going to change considerably even in case same input motion is used in the analysis.     

The comparison of hydrodynamic characteristics of karst aquifers: application on two karst formations in Zagros (Asmari and Ilam-Sarvak), southwest Iran

In order to study the function, hydrodynamic behavior, and hydraulic properties of the karst aquifers in Izeh, southwest Iran, time series analysis was applied to the precipitation, spring discharge, and piezometric head data of two representative karst systems of Zagros (Ilam-Sarvak and Asmari Formations). Time series analysis was applied to two karst aquifers, those of Asmari and Ilam-Sarvak Formations. The daily precipitations of anticlines were estimated based on the precipitation–elevation function which was applied on digital elevation model (DEM) of the area. The mean estimated daily precipitations were considered in bivariate time series analysis as input data of each karst system. The total length of time series was about 2.7 years, extending from May 2007 to December 2009. During the research, several one-parameter probe data loggers were installed, which daily measure the water surfaces in karst aquifers. Time series analysis was applied for describing Izeh karst aquifers with a focus on both univariate (autocorrelation and spectral analysis) and bivariate (cross-correlation, gain function, and coherency function) methods. The results show that Asmari karst aquifer in Kamarderaz Anticline has a large storage capacity. Because of lacking a well-organized karst network, in the Asmari karst aquifer, baseflow dominates with low contribution of quick-flow. In the Ilam-Sarvak karst aquifer (Shavish and Tanush Anticlines), the karstification occurred in fractures and small diameter conduits, which caused to quick-flow between dense limestone. The Ilam-Sarvak karst aquifer could be regarded as a transition between two extreme types of karst, e.g., highly karstified system and in the opposite, extremely diffused one. The analysis of well hydrograph in Ilam-Sarvak karst aquifer shows that the karst aquifer has a low storage capacity. Unlike Asmari karst aquifer, the fractures and small diameter conduits in Ilam-Sarvak karst aquifer are more enhanced, producing a better developed karst network. Contrary to the typical karst systems, however, diffuse flow and conduit flow coexist in the Asmari Formation.     

Analysis of rainfall preceding debris flows on the Smědavská hora Mt., Jizerské hory Mts., Czech Republic

In August 2010, extreme rainfall affected the north of the Czech Republic and caused regional floods and landslides. Three torrential debris flows originated in the Jizerské hory Mts., close to Bílý Potok on the north slope of the Smědavská hora Mt. The rainfall situation which triggered the debris flow was analyzed and compared with the rainfall situation in 1958 when a debris flow occurred in the same area. The rainfall data were obtained from rain gauges of the Czech Hydrometeorological Institute. Four rain gauges were chosen close to the Smědavská hora Mt. with data of daily amounts from 1983 to 2013 and 10-min intensity or hourly amounts from the specific period. The data from 1958 were available from three different rain gauges (only daily amounts). The data series were not complete so linear regression was applied to interpolate them. A number of analyses were carried out including daily rainfall, 2-day/3-day moving values, antecedent precipitation index (API) of 5/10/30 days, 10-min intensity, and hourly amounts, and the trigger factor of the debris flow in the study area was also investigated. It was determined that for the triggering of debris flows, both high API values as well as high-intensity short-duration rainfall is needed. It was documented that in cases of solely high API indices or high-intensity short-duration rainfalls, no debris flows were initiated.     

Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models

In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also compared with autoregressive integrated moving average (ARIMA) models. MLR attempts to model the relationship between two or more independent variables over a dependent variable by fitting a linear regression equation. The main aim of the present study is to see the consequences of development and applicability of simple models, when sufficient data length is available. Out of 47 years of daily historical rainfall and reservoir inflow data, 33 years of data is used for building the model and 14 years of data is used for validating the model. Based on the observed daily rainfall and reservoir inflow, various types of time-series, cause-effect and combined models are developed using lumped and distributed input data. Model performance was evaluated using various performance criteria and it was found that as in the present case, of well correlated input data, both lumped and distributed MLR models perform equally well. For the present case study considered, both MLR and ARIMA models performed equally sound due to availability of large dataset.     

The relation between karst spring discharge and rainfall by cross-correlation analysis (Campania, southern Italy)

The relation between rainfall and the discharge from two springs, located at the base of different karst massifs in southern Italy, is investigated by cross-correlation analyses. Data are derived from a continuous time window of 13 years. The input signal involves multiple rainfall time series (cumulative rainfall over varying time windows), while the time series of daily spring discharges are used as the output signal. Analyses were first conducted on the unprocessed data and then on data for which linear trends and seasonal components had been removed, the latter by a spectral analysis. Analyses contributed to the investigation of the time required for water to flow through the karst aquifers at the two sites. Long time intervals of the cumulative rainfall (>60 days) appear to be the main component affecting the spring discharge hydrographs; shorter time intervals seem to be related to quick-flow paths. Some statistics about the linear regression and the meaning of the cross-correlation analysis are discussed. Cross-correlation analysis can provide strong support for identification of the main rainfall contribution and the travel time through the main infiltration pathways in aquifers.     

Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June–September or JJAS) from 2005–2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall.     

TRMM3B42降雨数据在渭河流域的应用分析

运用渭河流域24个气象站点日降雨数据对2001~2012年热带测雨卫星(TRMM)3B42数据在不同子流域、不同降雨强度以及不同时间尺度的精度进行了对比验证,并对比分析了基于TRMM和站点数据的渭河流域降雨时空分布特征。结果显示:在不同子流域的日TRMM数据比站点观测数据对低值降雨更为敏感,而在极大值降雨数据观测上两者差距较大,月尺度TRMM站点观测数据确定性系数在0.89到0.96之间;两种数据在流域降雨的时空分布上表现一致性,在年内6月中旬~10月初为湿润多雨期,其余月份降雨较少,空间分布呈东南部大,西北部小的格局。     

中国西南地区冻雨灾害特征分析与评估

利用1961-2015年中国西南地区96个气象台站逐日气象观测资料,采用模糊信息分配法分析了我国西南地区出现冻雨天气时有利气象要素的变化规律。选取气温、湿度及日照时间确定了西南地区冻雨天气判断的评估标准：日平均气温≤ 2℃,日最高气温≤ 8℃,日最低气温≤ 0℃,相对湿度≥ 80%,日照时间≤ 1 h。通过重建发现发生冻雨的天数在11月-次年3月间呈现单峰型变化,其季节内冻雨日数的演变规律是少~多~少,每年的1月冻雨日数最多。经检验上述指标可用于重建西南地区各站点冻雨强度指数,并由此评估了西南地区冻雨灾害的时空分布状况。四川盆地南缘、云贵高原大部,以及湖南省东部地区冻雨指数大,表明该区域遭受冻雨灾害严重;青藏高原、川西高原地区气温虽低,但相对湿度小,日照时间长,均不满足冻雨条件,因此发生冻雨灾害的风险小。近年来我国西南地区冻雨强度总体呈现减弱的趋势。     

Spatio-temporal analysis of sub-hourly rainfall over Mumbai,India: Is statistical forecasting futile?

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006–2014 from these stations was performed; the 2013–2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.