Simulation of the direct runoff hydrograph at basin outlet

A simple model describing the transformation of effective rainfall to direct runoff through the overland flow mechanism is presented. The model is based on the classical representation of a watershed by a combination of planes and channels. The dynamics of overland flow in each plane is simulated by the non-linear kinematic wave, but the outflow from a given plane is concentrated in the middle of the corresponding drainage channel. The water routing in the channels is carried out by a piece-wise linearized formulation in space of the kinematic wave approximation. Using synthetic events on 10 watersheds, the model was tested by comparing it with results obtained by applying the non-linear kinematic wave to all the elements of the watershed. The model was found to be adequate, even in a form that simplifies the geometric features of the planes through an averaging procedure based on the Horton–Strahler ordering scheme of the watershed. © 1998 John Wiley & Sons, Ltd.     

Some features of the arid area variations over India: 1871–1984

Spatial variability of the annual rainfall over drier regions of India is studied by examining the variations in the arid areas. A long period (1871–1984) arid area series has been prepared for the entire country, including the two broad subregions of North India and Peninsular India, using annual rainfall data from 306 well distributed stations. Following an objectively determined criterion based on rainfall amount alone, the yearly area under arid conditions is obtained by totalling areas which received annual rainfall totals less than 560 mm. The interannual variability of the arid area series is large and its distribution is highly right-skewed, demonstrating large spatial variations in the annual rainfall over India. Statistical tests do not suggest any significant long-term trend in the arid area series, but persistently low values of the arid area after 1941 are noteworthy. Implications for the study of risk analysis and assessment of drought and desertification processes are discussed.     

Optimization of the raingauges for a representative all-India and subdivisional rainfall series

Summary An objective approach similar to the forward selection of independent variables in the multiple linear regression has been attempted to optimize the network of raingauges for the summer monsoon rainfall (June–September total) series (1871–1984) of India as well as its 29 selected meteorological subdivisions prepared involving the data of 306 raingauges. For the all-India monsoon rainfall series twenty seven gauges entered the selection whose mean showed the correlation coefficient (CC) of 0.9869. Keeping in view the difficulties of getting data from all the 306 gauges, 35 India Meteorological Department (IMD) gauges with mean showing CC of 0.9898 have been identified for updating this series. The constructed all-India monsoon rainfall series for the period 1871–1992 using 35 selected observations is presented. It was interesting to note that the set of 35 gauges selected for the monsoon total has shown equally promising results for the all-India monsoon monthly (June–September) as well as the annual rainfall series.For the 29 subdivisional monsoon rainfall series, however, in total 188 IMD-gauges (62% of the total of 306 gauges) entered the selection. For 17 subdivisions the CC exceeded 0.98, for 3 subdivisions it varied between 0.97 and 0.98, for 5 subdivisions between 0.96 and 0.97 and for the remaining 4 subdivisions between 0.90 and 0.94. They showed equally encouraging results for the monsoon monthly and annual rainfall series for the different subdivisions.Limitations and implications of the optimization technique are also briefly discussed.With 9 Figures     

Effect of counter-gradient in the computation of turbulent fluxes of heat and moisture in a regional model

The counter-gradient terms in the computations of turbulent fluxes of heat and moisture have been included in the PBL parameterization of a regional model for monsoon prediction. Results show that inclusion of counter-gra-dient terms has a marginal impact in the prediction of large scale monsoon circulation and rainfall rates.     

Empirical Orthogonal Function (EOF) analysis of monsoon rainfall and satellite-observed outgoing long-wave radiation for Indian monsoon: a comparative study

Summary The present study involves the use of Empirical Orthogonal Function (EOF) analysis/Principal Component Analysis (PCA) to compare the dominant rainfall patterns from normal rainfall records over India, coupled with the major modes of the Outgoing Long-wave Radiation (OLR) data for the period (1979–1988) during the monsoon period (June–September). To understand the intraseasonal and interannual variability of the monsoon rainfall, daily and seasonal anomalies have been obtained by using the (EOF) analysis. Importantly, pattern characteristics of seasonal monsoon rainfall covering 68 stations in India are highlighted.The purpose is to ascertain the nature of rainfall distribution over the Indian continent. Based on this, the percentage of variance for both the rainfall and OLR data is examined. OLR has a higher spatial coherence than rainfall. The first principal component of rainfall data shows high positive values, which are concentrated over northeast as well as southeast, whereas for the OLR, the area of large positive values is concentrated over northwest and lower value over south India apart from the Indian ocean. The first five principal components explain 92.20% of the total variance for the rainfall and 99.50% of the total variance for the outgoing long-wave radiation. The relationship between monsoon rainfall and Southern Oscillations has also been examined and for the Southern Oscillations, it is 0.69 for the monsoon season. The El-Niño events mostly occurred during Southern Oscillations, i.e. Walker circulation. It has been found that the average number of low pressure system/low pressure system days play an important role during active (flood) or inactive (drought) monsoon year, but low pressure system days play more important role in comparison to low pressure systems and their ratio are (16:51) and (13:25) respectively. Significantly, the analysis identifies the spatial and temporal pattern characteristics of possible physical significance.     

Study of terrestrial carbon flux by eddy covariance method in revegetated manganese mine spoil dump at Gumgaon,India

The micrometeorological technique of eddy covariance is a powerful tool for characterizing the carbon (C) budget of terrestrial ecosystems. Eddy covariance method was used for estimating Net Ecosystem Exchange (NEE) of carbon dioxide between atmosphere and revegetated manganese mine spoil dump at Gumgaon, India. In this paper, we analyzed the diel CO₂ flux pattern and its response to various physical environmental conditions. The carbon balance of terrestrial ecosystems is particularly sensitive to climatic changes. Study of diel pattern of CO₂ flux showed that carbon uptake was dependent on sunlight. Effect of temperature and latent heat on the CO₂ flux showed that rate of CO₂ uptake increased proportionally, but later declined due to various factors like stomatal response, high evaporative demand, circadian rhythm and/or a combination of all three. Net ecosystem production of revegetated land was found to be 28.196 KgC/ha/day whereas average net carbon release by the ecosystem, through respiration was observed to be 5.433 KgC/ha/day. Thus, quantifying net carbon (C) storage in degraded land is a necessary step in the validation of carbon sequestration estimates and in assessing the possible role of these ecosystems in offsetting adverse impacts of fossil fuel emissions.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Interannual variability and predictability of sea level along the Indian Coast

Summary The Indian coast stretching more than 7,500 km constitutes the major portion of the South Asian coastline in the North Indian Ocean region. The South Asian region is significantly influenced by meteorological/oceanographic phenomena like monsoons, El Ni?o/Southern Oscillation (ENSO) and tropical cyclones. Direct/indirect impacts of these phenomena, which exhibit large interannual variabilities, on sea level changes in this region are considerable. Our results show that the mean sea level along the eastern coast of India, which is highly vulnerable to the incidence of severe tropical cyclones, is considerably higher than normal during the intense cyclonic period of a year falling in the positive phase of the Southern Oscillation (La Ni?a epoch), thereby enhancing the hazardous potential of tropical cyclones. Further, in the closing phase of the La Ni?a southwest monsoon, higher sea level anomalies prevail along the Indian coast raising the flooding potential of such monsoons. Over the west coast of India significant simultaneous correlations have been found between the amount of southwest monsoon rainfall and the mean sea level during the period from June to September. Over the east coast of India at Visakhapatnam, mean sea level is predictable with a fair degree of confidence one month in advance, by using the Sea Surface Temperature (SST) and the Southern Oscillation Index (SOI) as predictors. These results will be useful in the annual preparedness programmes aimed at mitigating the impacts of natural disasters like tropical cyclones and floods in the South Asian region. Received November 9, 2001