Ravinder Kaur

Integration of linear programming and a watershed-scale hydrologic model for proposing an optimized land-use plan and assessing its impact on soil conservation—A case study of the Nagwan watershed in the Hazaribagh district of Jharkhand, India

The present investigation was an attempt to develop a Spatial Decision Support System (SDSS) for a test Nagwan watershed situated in the Damodar–Barakar catchment in India, the second most seriously eroded area in the world, for not only estimating sediment yields under prevailing resource management systems but also designing a linear programming (LP)-based optimized land-use plan for soil loss reduction in the test watershed. The proposed SDSS was validated on 9 years (1981–1983, 1985–1989, and 1991) of sediment yield data for the test watershed. This showed that the SDSS could mimic the annual dynamics of the total sediment yields at the test watershed outlet with a correlation coefficient of 0.65, model efficiency coefficient of 0.70, mean relative error of −17.97%, and root mean square prediction error of 9.63 t ha−1. It could also be used as an efficient tool for assessing sediment yields from different parts of the test watershed and for designing a linear programming (LP)-based optimized land-use plan for reduced total sediment yields from the test watershed. The LP-based land-use plan proposed no change in the total areas under paddy, corn, and forest land-use types but suggested their re-distribution within the test watershed, thereby leading to not only a reduction in the test watersheds total sediment yield by about 14.61% but also an increase in its paddy and corn crop productivities by 2.80 and 68.14%, respectively. The proposed LP-based land-use plan for the test watershed could thus lead to an enhanced productivity benefit of about Rs 3735 ha−1, in monetary terms, from corn crop cultivation at its optimal locations.

Low-Cost Remediation and On-Farm Management Approaches for Safe Use of Wastewater in Agriculture

As freshwater sources become scarcer, wastewater use has become an inevitable and attractive option for conserving and expanding available water supplies worldwide. In low-income countries where urban agriculture provides livelihood opportunities and food security, irrigation is the most prominent and the most rapidly expanding use of wastewater. Even though the opportunities like reliable resource for supporting livelihoods and improving living standards for the urban poor are coupled with wastewater irrigation, still some risks cannot be neglected. Wastewater is a serious source of contamination for natural resources and disproportionally affects farmers and consumers due to microbial and chemical health risks. By adopting strategic risk assessment and management, framework allows reducing risks associated with wastewater irrigation. A combination of management and treatment measures which are low cost, low tech, and eco-friendly along with strategically focused policies and action plans needs to be formulated for safe and sustainable use of wastewater.

Ground validation of an algorithm for estimating surface suspended sediment concentrations from multi-spectral reflectance data

Pollution of water resources by sediments eroded from degraded watersheds is a critical concern around the world. Current methods for locating these eroding areas and off-site damage to water resources through visual observations and field sampling with subsequent laboratory analysis are time consuming and expensive. There is thus, a justified interest in developing algorithms for quick estimation of suspended sediment concentrations in large water-bodies from remotely sensed data.This paper presents the results of a ground validation study on characterization and quantification of surface suspended sediment concentrations (SSC) in sediment laden water bodies through an n-waveband specific numerical index, total information content. A comparison of SSC-predictive potential of the proposed new index, derived from four broad (100–300 nm) Landsat MSS, five broad (40–300 nm) Landsat TM and eight narrow (20–40 nm) IRS-P4 OCM spectral bands, with that of the conventional (NIR-Red and NIR+Red) indices, computed from the same spectral band data, is also presented. The study reveaied that at SSCs 250 mg/1, the proposed index (derived from either broad / narrow landsat MSS/TM or IRS-P4 OCM spectral data) could lead to SSC predictions (with mean errors within 20%) comparable with those obtained with the conventional indices (derived from the same spectral band data). It could further be observed that, in general, lower sediment concentrations (i.e. SSCs 150 mg/1) were associated with higher prediction inaccuracies. A comparison of the mean errors of predictions associated with the proposed and the conventional (NIR-Red and NIR+Red) indices computed from broad and narrow band data for SSCs 150 mg/I, revealed that an increase in number of wavebands (from 4 MSS to 5 TM or 8 OCM bands) and a decrease in the bandwidth of these wavebands (from broad MSS/ TM bands to narrow OCM bands) led to a significant increase in the prediction accuracy of the proposed new index. These prediction accuracies were observed to be the highest with the proposed index calculated from narrow OCM-P4 spectral data. However this could not be observed with the conventional indices at any of the SSC ranges and with the proposed index at SSCs 250 mg/l. This shows that the lower SSC-predictive potential of proposed index was a significant function of both the number and the bandwidth of spectral bands used for its computation. In fact in one of the cases, lower SSC (150 mg/l) -predictive accuracy of the proposed index was found to be significantly higher than that of the conventional (NIR+R) index.The proposed algorithm could thus compress the information contained in the entire reflectance spectrum of the sediment laden water bodies to their sediment type and concentration specific characteristic values. This characteristic of the proposed index was not shared by any of the conventional indices, based on only two waveband data. In fact the proposed index appears to be the only mean of completely compressing and quantifying the information contained in all the information channels of a narrow band spectrometer (consisting of 200 wavebands) to be shortly launched by ISRO for satellite based inventory of natural resources.

A numerical technique for delineation of soil mapping units using multi-spectral remote sensing data

A numerical technique for transformation of ground based sail spectral information into soil mapping — unit information, in terms of the total information content index has been proposed. The study carried out on 14 surface soil samples. widely differing in their physical appearance of colour and collected from different parts of India, revealed that total information content index could distinctly discriminate between the contrasting soil physiographic units with black cotton, red and sandy soil types. A comparison of the proposed index with the conventionally used two or three waveband specific indices (e.g. NIR/Red and NIR-Red/Red-Green) showed that the proposed index was more characteristic of the various soil types studied. Further, unlike the conventional 2-D indices, the proposed, numerical technique lead to the complete compression of the information contained in the entire reflectance spectrum (irrespective of the number of wavebands) to a single characteristic value in 1-D Space and a simplified 1-D clustering analysis.

Modelling approaches for simulating wetland pollutant dynamics

ABSTRACT A number of black box and process-based modelling approaches, their strengths/limitations, and future applications for simulating contaminant dynamics in constructed wetlands (CWs) have been reviewed. Scanning of literature reveals that most of the CW modelling approaches are limited to the simulation of only nutrient and organic pollutant load dynamics. Performance analysis of the various process/black box-based models for simulating pollutant dynamics in vertical subsurface flow, horizontal subsurface flow, and hybrid CW systems further reveals that most of the existing modelling approaches have not not so far been able to account for the changing climatic conditions and the heavy metal dynamics. The paper thus highlights the gaps in the knowledge in the current state of the art for simulating wetland pollutant dynamics and suggests mechanisms for increasing the scope of such modelling approaches in the proper design and operation of the CW systems.