A drought frequency formula

Abstract

The important elements of a drought phenomenon are the longest duration and the largest severity for a desired return period. These elements form a basis for designing water storage systems to cope with droughts. At times, a third element, drought intensity, is also used and is defined as the ratio of severity to duration. The commonly available statistics for the causative drought variables such as annual rainfall or runoff sequences are the mean, the coefficient of variation and the lag one serial correlation coefficient, and occasionally some indication of the probability distribution function (pdf) of the sequences. The extremal values of the duration and severity are modelled in the present paper using information on the aforesaid parameters at the truncation level equal to the mean of the drought sequence, which is generally taken as the truncation level in the analysis of droughts. The drought severity has been modelled as the product of the duration and intensity with the assumption of independence between them. An estimate of drought intensity has been realized from the concept of the truncated normal distribution of the standardized form of the drought sequences in the normalized domain. A formula in terms of the extremal severity and the T-year return period has been suggested similar to the flood frequency formulae, commonly cited in hydrological texts.     

Flash flood of July 1979 in the Luni basin—a rare event in the Indian desert

ABSTRACT

A well marked low pressure monsoon depression caused unprecedented heavy rainfall of five days duration (15–19 July 1979) in the Luni basin in the India arid zone. It caused the worst flash flood in living memory. Saturated antecedent soil moisture conditions, thin soil cover underlain by bed rock or hardpan, a larger area of exposed rocks in the basin and failure of the earthen reservoirs further worsened the flood effect. During flooding, suspended sediment concentrations rose from 0.86 to 40.2 g 1^?1 downstream due to bank scouring, erosion and high transmission losses of the runoff volume in the alluvial channels. The dilution effect of flooding caused lower concentrations of the total dissolved solids which increased with downstream travel. Social effects of this flood and consequences on future planning in the Luni basin have also been discussed.     

Role of convective and microphysical processes on the simulation of monsoon intraseasonal oscillation

Climate Dynamics - The study explores the role of ice-phase microphysics and convection for the better simulation of Indian summer monsoon rainfall (ISMR) and monsoon intraseasonal oscillation...     

Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias

We have evaluated the simulation of Indian summer monsoon and its intraseasonal oscillations in the National Centers for Environmental Prediction climate forecast system model version 2 (CFSv2). The dry bias over the Indian landmass in the mean monsoon rainfall is one of the major concerns. In spite of this dry bias, CFSv2 shows a reasonable northward propagation of convection at intraseasonal (30–60 day) time scale. In order to document and understand this dry bias over the Indian landmass in CFSv2 simulations, a two pronged investigation is carried out on the two major facets of Indian summer monsoon: one, the air–sea interactions and two, the large scale vertical heating structure in the model. Our analysis shows a possible bias in the co-evolution of convection and sea surface temperature in CFSv2 over the equatorial Indian Ocean. It is also found that the simulated large scale vertical heat source (Q1) and moisture sink (Q2) over the Indian region are biased relative to observational estimates. Finally, this study provides a possible explanation for the dry precipitation bias over the Indian landmass in the simulated mean monsoon on the basis of the biases associated with the simulated ocean–atmospheric processes and the vertical heating structure. This study also throws some light on the puzzle of CFSv2 exhibiting a reasonable northward propagation at the intraseasonal time scale (30–60 day) despite a drier monsoon over the Indian land mass.     

QUANTITATIVE ANALYSIS OF TRACE ELEMENTS IN GEOLOGICAL MATERIALS BY LASER ABLATION ICPMS: INSTRUMENTAL OPERATING CONDITIONS AND CALIBRATION VALUES OF NIST GLASSES

A UV laser ablation microprobe coupled to an ICPMS has been used to determine trace element concentrations in solids with a spatial resolution of 50 microns and detection limits ranging from 2 μg/g for Ni to 50 ng/g for the REE, The, and U. Experiments designed to optimize laser operating conditions show that pulse rates of 4 Hz produce a steady state signal with less inter-element fractionation per unit time than higher pulse rates (10–20 Hz). Comparisons of laser microprobe analyses of garnets and pyroxenes using the NIST 610 and 612 glasses as calibration standards, with proton microprobe, solution ICPMS, INAA and XRF data show no significant matrix effects. Laser microprobe analyses of the NIST 610 and 612 glasses have a precision and accuracy of 2–5%, and error analysis shows that counting statistics and the precision on the internal standard concentration accounts for the analytical uncertainty. The NIST glasses appear to be useful calibration materials for trace element analysis of geological materials by laser microprobe.     

BICUBIC SPLINE INTERPOLATION: A QUANTITATIVE TEST OF ACCURACY AND EFFICIENCY*

Two different methods for the construction of an approximation to bicubic splines for interpolating irregularly spaced two-dimensional data are described. These are referred to as the least squares line (LSL) and linear segment (LINSEG) construction procedures. A quantitative test is devised for investigating the absolute accuracy and efficiency of the two spline interpolation procedures. The test involves (i) laying of artificial flight lines on the analytically known field of a model, (ii) interpolation of field values along the flight lines and their subtraction from the original field values to compute the residuals. This test is applied on fields due to four models (three prism models and one dyke model) placed at different depths below the flight lines, and for each case the error estimates (the mean error, the maximum error and the standard deviation) are tabulated. An analysis of the error estimates shows in all cases the LSL interpolation to be more accurate than the LINSEG, although the latter is about 50% faster in computer time. The relative accuracy and efficiency of the LSL interpolation is also tested against a recent method based on harmonization procedure, which shows the latter to be more precise, though much slower in speed.     

Groundwater level estimation in northern region of Bangladesh using hybrid locally weighted linear regression and Gaussian process regression modeling

Theoretical and Applied Climatology - Urban groundwater resources (GWRs) have declined substantially in recent decades, due to rapid urbanization, population growth, groundwater exploitation, land...     

Modelling of piping collapses and gully headcut landforms:Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)tech-niques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable's importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model's result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.