H. Raman

Bio: H. Raman is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Routing (hydrology) & Decision support system. The author has an hindex of 2, co-authored 3 publications receiving 39 citations.

Decision Support System for Crop Planning during Droughts

Abstract: Demand for water is increasing continually, whereas available supplies are more or less constant. Under these circumstances there is an urgent need to introduce efficient techniques in water resources management for optimal utilization of available water. Water management under drought conditions assumes great importance in a tropical region such as India, where one‐third of the cropped area is affected by frequent droughts. This paper deals with the development and application of an expert system for drought management. A linear programming model was used to generate optimal cropping patterns from past drought experiences as also from synthetic drought occurrences. These policies together with the knowledge of the experts were incorporated in an expert system. Using this, one can identify the degree of drought in the current situation and its similarity to the identified drought events and be able to get the corresponding management strategy.

Decision Support System for Water Supply Management

Abstract: Water supply management is one area in which subjective decision making becomes necessary. Knowledge based decision support system is proposed for use in operation and management of an existing water supply system in South India. The task considered includes forecasting the future demand for water supply using time series, analysing the water supply network to identify the problem areas using WADISO program and an optimization Model to evolve management strategies.

Development of an Expert System for Flood Management

Abstract: An expert system for flood management is developed for the flood control operation of a reservoir. The procedure uses both expert system tools and traditional computer programming techniques considering the complexity of the reservoir operation problem. The present work has been carried out in four phases, namely, flood estimation, flood simulation, reservoir operation, and expert system development. In the flood simulation phase, rainfall-runoff computation model, and model for computing water surface profiles have been utilized. The use of the developed system is demonstrated with a case study of the Adyar river in the Madras metropolitan city to evolve the safe releases that can be followed during flood considering the reservoir inflows and the overland flow from the urban drainage area. The developed expert system could be a valuable tool in reservoir operation decision-making and thereby help in minimizing the flood damages in the Adyar river flood plains.

Numerical Modeling of Wheat Irrigation using Coupled HYDRUS and WOFOST Models

Abstract: To efficiently manage water resources in agriculture, the hydrologic model HYDRUS-1D and the crop growth model WOFOST were coupled to improve crop production prediction through accurate simulations of actual transpiration with a root water uptake method and soil moisture profile with the Richards equation during crop growth. An inverse modeling method, the shuffled complex evolution algorithm, was used to identify soil hydraulic parameters for simulating the soil moisture profile. The coupled model was validated by experimental study on irrigated wheat (Triticum aestivum L.) in the middle reaches of the Heihe River, northwest China, in a semiarid and arid region. Good agreement was achieved between the simulated actual evapotranspiration, soil moisture, and crop production and their respective field measurements under a realistic irrigation scheme. A water stress factor, actual root uptake with potential transpiration, is proposed as an indicator to guide irrigation. Numerical results indicated that the irrigation scheme guided by the water stress factor can save 27% of irrigation water compared with the current irrigation scheme. Based on the calibrated model, uncertainty and sensitivity analysis methods were used to predict the risk of wheat production loss with decreasing irrigation and to study the effects of coupled model parameters and environmental factors on wheat production. The analysis revealed that the most suitable groundwater depth for wheat growth is 1.5 m. These results indicate that the coupled model can be used for analysis of schemes for saving water and study of the interaction between crop growth and the hydrologic cycle.

Irrigation Planning Under Uncertainty—A Multi Objective Fuzzy Linear Programming Approach

Abstract: The problem of irrigation planning becomes more complex by considering an uncertainty. The uncertainties can be tackled by formulating the problem of irrigation planning as Fuzzy Linear Programming (FLP). FLP models can incorporate the scenario of real world problem. In the present study, Multi Objective Fuzzy Linear Programming (MOFLP) irrigation planning model is formulated for deriving the optimal cropping pattern plan for the case study of Jayakwadi project in the Godavari river sub basin in Maharashtra State, India. Four conflicting objectives are considered such as Net Benefits (NB), Crop/Yield Production (CP), Employment Generation/Labour Requirement (EG) and Manure Utilization (MU). Four different cases are considered to incorporate the uncertainty in MOFLP model. To include the uncertainty in irrigation planning problem only objectives are taken as fuzzy and constraints are crisp in nature in Case-I. To consider the uncertainty involved in availability of resources, in Case-II the stipulations are fuzzy. The technological coefficients are fuzzy in Case-III. The Case-IV includes both technological coefficients and stipulations fuzzy. The level of satisfaction (λ) works out to be 0.58, 0.50, 0.50 and 0.28 respectively for Case-I to IV. The results obtained in Case-IV are more realistic and promising as it involves the uncertainty in technological coefficients and stipulations simultaneously.