Impact of surface meteorological observations on RAMS forecast of monsoon weather systems over the Indian region

Summary An attempt has been made to study the impact of surface meteorological observations on the Regional Atmospheric Modelling System (RAMS) simulation of a monsoon depression and two low pressure systems. The surface observations are blended with the GEWEX Asian Monsoon Experiment (GAME) gridded analyses for these cases. In one set of experiments the model is run in 12 hour nudging mode initially and then in forecast mode using GAME gridded data without incorporating surface observations. In another set of experiments surface data are incorporated to enhance the signature of the systems in the large scale GAME analyses and nudging is applied initially for twelve hours. Subsequently the model is run in forecast mode to see the temporal and spatial evolution of different meteorological features associated with the systems. It is found that inclusion of the surface data has in general enhanced the signature of the systems in the analysis and subsequently shows improvement in the forecast of sea-level pressure, geopotential, wind field, etc. and the associated forecast of heavy rainfall, in particular. To make a quantitative comparison of the predicted rainfall with the observed one, equitable threat score and bias are calculated for different threshold values of rainfall. It is clearly noted that inclusion of surface data has improved the precipitation forecast over the Indian land mass as indicated by the equitable threat score and bias for all the threshold rainfall categories.     

Agricultural management impacts on groundwater: simulations of existing and alternative management options in Peninsular India

Understanding the principal causes and possible solutions for groundwater depletion in India is important for its water security, especially as it relates to agriculture. A study was conducted in an agricultural watershed in Andhra Pradesh, India to assess the impacts on groundwater of current and alternative agricultural management. Hydrological simulations were used as follows: (1) to evaluate the recharge benefits of water‐harvesting tillage through a modified Soil and Water Assessment Tool (SWAT) model and (2) to predict the groundwater response to changing extent and irrigation management of rice growing areas. The Green–Ampt infiltration routine was modified in SWAT was modified to represent water‐harvesting tillage using maximum depression storage parameter. Water‐harvesting tillage in rainfed croplands was shown to increase basin‐scale groundwater recharge by 3% and decrease run‐off by 43% compared with existing conventional tillage. The groundwater balance (recharge minus irrigation withdrawals), negative 11 mm/year under existing management changed to positive (18–45 mm/year) when rice growing areas or irrigation depths were reduced. Groundwater balance was sensitive to changes in rice cropland management, meaning even small changes in rice cropland management had large impacts on groundwater availability. The modified SWAT was capable of representing tillage management of varying maximum depression storage, and tillage for water‐harvesting was shown to be a potentially important strategy for producers to enhance infiltration and groundwater recharge, especially in semi‐arid regions where rainfall may be becoming increasingly variable. This enhanced SWAT could be used to evaluate the landscape‐scale impacts of alternative tillage management in other regions that are working to develop strategies for reducing groundwater depletion. Copyright © 2013 John Wiley & Sons, Ltd.     

Stability analysis of multi-directional anchored rock slope subjected to surcharge and seismic loads

More than one set of anchors with different orientations can be an economical solution to completely stabilize the rock slope. In this note, a general analytical expression for the factor of safety of a multi-directional anchored rock slope (MDARS) against plane failure is derived, incorporating most of the practically occurring destabilizing forces under surcharge and seismic loading conditions. Several special cases of this expression are found to be similar to those reported in the literature. A graphical presentation shows that for any specific inclination of one set of anchors to the normal at failure plane, the variation in the inclination of the second set of anchors to the normal at failure plane, when greater than approximately 60°, does not cause a significant change in the factor of safety of the MDARS.     

Eddy covariance‐based evapotranspiration for a subtropical wetland

The eddy covariance (EC) method was used in a 30‐month study to quantify evapotranspiration (ET) and vegetation coefficient (K_CW) for a wetland on a ranch in subtropical south Florida. To evaluate the errors in ET estimates, the EC‐based ET (ET_C‐EC) and the Food and Agricultural Organization (FAO) Penman–Monteith (PM) based ET (ET_C‐PM) estimates (with literature crop coefficient, K_C) were compared with each other. The ET_C‐EC and FAO‐PM reference ET were used to develop K_CW. Regression models were developed to estimate K_CW using climatic and hydrologic variables. Annual and daily ET_C‐EC values were 1152 and 3.27 mm, respectively. The FAO‐PM model underestimated ET by 25% with ET_C‐EC being statistically higher than ET_C‐PM. The K_CW varied from 0.79 (December) to 1.06 (November). The mean K_CW for the dry (November–April) season (0.95) was much higher than values reported for wetlands in literature; whereas for the wet (May–October) season, K_CW (0.97) was closer to literature values. Higher than expected K_CW values during the dry season were due to higher temperature, lower humidity and perennial wetland vegetation. Regression analyses showed that factors affecting the K_CW were different during the dry (soil moisture, temperature and relative humidity) and wet (net radiation, inundation and wind speed) seasons. Separate regression models for the dry and wet seasons were developed. Evapotranspiration and K_CW from this study, one of the first for the agricultural wetlands in subtropical environment, will help improve the ET estimates for similar wetlands. Copyright © 2013 John Wiley & Sons, Ltd.     

A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.

The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.     

Winter fog over the Indo-Gangetic Plains: mapping and modelling using remote sensing and GIS

Almost every year in the winter months (December–February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005–06, 2006–07 and 2007–08, the fog-affected area has been found to cover about 575,800 km², 594,100 km² and 478,000 km², respectively. Less fog in 2007–08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3–13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images.