Desertification in western Rajasthan (India): an assessment using remote sensing derived rain-use efficiency and residual trend methods

Natural Hazards - Owing to its impact on global ecosystem, climate change and related effects is being perceived as a serious issue worldwide especially in the arid and semi-arid regions. Climatic...     

Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs

Digital Elevation Model (DEM) is one of the important parameters for soil erosion assessment. Notable uncertainties are observed in this study while using three high resolution open source DEMs. The Revised Universal Soil Loss Equation (RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs (SRTM, ASTER and CARTOSAT) and their increasing grid space (pixel size) from the actual. The study area is a part of the Narmada river basin in Madhya Pradesh state, which is located in the central part of India and the area covered 20,558 km². The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90, 150, 210, 270 and 330 m for this study. Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map (toposheet). Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL (Mean Sea Level), before the accuracy assessment and modelling. Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31, 14.51, and 18.19 m in 30, 150 and 330 m resolution respectively, is better than the ASTER and the CARTOSAT DEMs. When the grid space of the DEMs increases, the accuracy of the elevation and calculated soil erosion decreases. This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models. The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.     

Prediction of velocity-dip-position over entire cross section of open channel flows using entropy theory

An analytical model to predict the velocity-dip-position is presented in this study. Unlike the previous studies where empirical or semiempirical models were suggested, in this study the model is derived by using entropy theory. Using the principle of maximum entropy, the model for dip-position is derived by maximizing the Shannon entropy function after assuming dimensionless dip-position as a random variable. No estimation of empirical parameter is required for calculating dip-position from the proposed model. The model is capable of predicting the velocity-dip-position at any section from sidewall region (along lateral direction) of an open channel with any aspect ratio. The ratio of mean to maximum value of dip-position is analyzed from data, and it is found that ratio is almost constant for narrow open channels and it increases with aspect ratio for wide open channels. A relation is also proposed to predict this ratio in case of wide open channels. The developed model of velocity-dip-position is tested with existing experimental data for a wide range of aspect ratio and is also compared with other empirical models. The present model shows good agreement with the observed data and is comparable with the existing models.     

Optimization of groundwater level monitoring network using GIS-based geostatistical method and multi-parameter analysis: A case study in Wainganga Sub-basin,India

Groundwater is one of the most important resources, its monitoring and optimized management has now become the priority to satisfy the demand of rapidly increasing population. In many developing countries, optimized groundwater level monitoring networks are rarely designed to build up a strong groundwater level data base, and to reduce operation time and cost. The paper presents application of geostatistical method to optimize existing network of observation wells for 18 sub-watersheds within the Wainganga Sub-basin located in the central part of India. The average groundwater level fluctuation (GWLF) from 37 observation wells is compared with parameters like lineament density, recharge, density of irrigation wells, land use and hydrogeology (LiRDLH) of Wainganga Sub-basin and analyzed stochastically in Geographic Information System (GIS) environment using simple, ordinary, disjunctive and universal kriging methods. Semivariogram analyses have been performed separately for all kriging methods to fit the best theoretical model with experimental model. Results from gaussian, spherical, exponential and circular theoretical models were compared with those of experimental models obtained from the groundwater level data. Spatial analyses conclude that the exponential semivariogram model obtained from ordinary kriging gives the best fit model. Study demonstrates that ordinary kriging gives the optimal solution and additional number of observation wells can be added utilizing the error variance for optimal design of groundwater level monitoring networks. This study describes the use of Geostatistics methods in GIS to predict the groundwater level and upgrade groundwater level monitoring networks from the randomly distributed observation wells considering multiple parameters such as GWLF and LiRDLH. The method proposed in the present study is observed to be an efficient method for selecting observation well locations in a complex geological set up. The study concludes that minimum 82 wells are required for proper monitoring of groundwater level in the study area.     

The rapid growth and decay of severe cyclone JAL (2010) over the Bay of Bengal

This study investigates the life cycle of Bay of Bengal cyclone JAL, characterized by a rapid fluctuation in its intensity during 60-h interval. The cyclone JAL underwent a period of rapid intensification during 24-h from 0000 UTC 05 November to 0000 UTC 06 November 2010. It was quasi-static during subsequent 24 h followed by a 12-h period of unusually rapid decay. During the rapid cyclogenesis phase, the system intensified (by 25 kt) from deep depression (DD) to severe cyclonic storm (SCS) and weakened (by 30 kt) from SCS to DD during the 12-h period of rapid cyclolysis. European Centre for Medium Range Weather Forecasts (ECMWF) model analysis field is used to analyze the Q vectors, K index and potential vorticity (PV) to diagnose the life cycle of this unusual cyclone. The analysis reveals that the 500–700 hPa column-averaged Q-vector convergence above the surface cyclone had strengthened and very high values of the K index produced a burst of heavy precipitation during the development stage of the cyclone. The associated latent heat release produced a substantial diabatic positive PV anomaly in the lower and middle troposphere that caused rapid cyclogenesis. The rapid cyclolysis is coincident with the weakening of the upper and lower PV anomalies and the westward shearing of the upper PV from the cyclone centre. Thus, the very latent heat release that assisted the rapid development of the cyclone also played an important role in its subsequent rapid decay. ECMWF model forecast for track and intensity is also verified.