Regional Differences in the Influence of Irrigation on Climate

A global climate model experiment is performed to evaluate the effect of irrigation on temperatures in several major irrigated regions of the world. The Community Atmosphere Model, version 3.3, was modified to represent irrigation for the fraction of each grid cell equipped for irrigation according to datasets from the Food and Agriculture Organization. Results indicate substantial regional differences in the magnitude of irrigation-induced cooling, which are attributed to three primary factors: differences in extent of the irrigated area, differences in the simulated soil moisture for the control simulation (without irrigation), and the nature of cloud response to irrigation. The last factor appeared especially important for the dry season in India, although further analysis with other models and observations are needed to verify this feedback. Comparison with observed temperatures revealed substantially lower biases in several regions for the simulation with irrigation than for the control, suggesting that the lack of irrigation may be an important component of temperature bias in this model or that irrigation compensates for other biases. The results of this study should help to translate the results from past regional efforts, which have largely focused on the United States, to regions in the developing world that in many cases continue to experience significant expansion of irrigated land.

Side Chain Structure Determines Unique Physiologic and Therapeutic Properties of norUrsodeoxycholic Acid in Mdr2(-/-) Mice

24-norursodeoxycholic acid (norUDCA), a side chain-modified ursodeoxycholic acid derivative, has dramatic therapeutic effects in experimental cholestasis and may be a promising agent for the treatment of cholestatic liver diseases. We aimed to better understand the physiologic and therapeutic properties of norUDCA and to test if they are related to its side chain length and/or relative resistance to amidation. For this purpose, Mdr2-/- mice, a model for sclerosing cholangitis, received either a standard diet or a norUDCA-, tauro norursodeoxycholic acid (tauro- norUDCA)-, or di norursodeoxycholic acid (di norUDCA)-enriched diet. Bile composition, serum biochemistry, liver histology, fibrosis, and expression of key detoxification and transport systems were investigated. Direct choleretic effects were addressed in isolated bile duct units. The role of Cftr for norUDCA-induced choleresis was explored in Cftr-/- mice. norUDCA had pharmacologic features that were not shared by its derivatives, including the increase in hepatic and serum bile acid levels and a strong stimulation of biliary HCO3- -output. norUDCA directly stimulated fluid secretion in isolated bile duct units in a HCO3- -dependent fashion to a higher extent than the other bile acids. Notably, the norUDCA significantly stimulated HCO 3- -output also in Cftr-/- mice. In Mdr2-/- mice, cholangitis and fibrosis strongly improved with norUDCA, remained unchanged with tauro- norUDCA, and worsened with di norUDCA. Expression of Mrp4, Cyp2b10, and Sult2a1 was increased by norUDCA and di norUDCA, but was unaffected by tauro- norUDCA. Conclusion:The relative resistance of norUDCA to amidation may explain its unique physiologic and pharmacologic properties. These include the ability to undergo cholehepatic shunting and to directly stimulate cholangiocyte secretion, both resulting in a HCO3- -rich hypercholeresis that protects the liver from cholestatic injury.

Ways and Means for Disposal of Surplus Water in Storage Reservoirs and other Irrigation and Flood Protective Works

In the paper new way of classifying spillways have been suggested. The various types, merits and demerits or existing spillway devices have been discussed. The considerations governing the choice of a design of a spillway have been mention. A criteria for working out the economics of spillway design has been suggested. An efficient surplus sing device has next been described and compared with other devices. In conclusion it has been suggested that the most efficient and at the same time economical arrangement will be a combination of devices. In conclusion it has been suggested will be a combination of crest gate, volute siphons and high head gates. The appendix gives a list of devices used in dams in various parts of the world.

Computer-model for vedavati groundwater basin .3. Irrigation potential

An estimate of the irrigation potential over and above the existing utilization was made based on the ground water potential in the Vedavati river basin. The estimate is based on assumed crops and cropping patterns as per existing practice in the various taluks of the basin. Irrigation potential was estimated talukwise based on the available ground water potential identified from the simulation study. It is estimated that 84,100 hectares of additional land can be brought under irrigation from ground water in the entire basin.

Multiobjective Analysis of Irrigation Planning in River Basin Development

A river basin that is extensively developed in the downstream reaches and that has a high potential for development in the upper reaches is considered for irrigation planning. A four-reservoir system is modeled on a monthly basis by using a mathematical programing (LP) formulation to find optimum cropping patterns, subject to land, water, and downstream release constraints. The model is applied to a fiver basin in India. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analyzed in the context of multiobjective planning, and the tradeoffs are discussed.

Optimal irrigation planning in river basin development: The case of the Upper Cauvery river basin

The study deals with the irrigation planning of the Cauvery river basin in peninsular India which is extensively developed in the downstream reaches and has a high potential for development in the upper reaches. A four-reservoir system is modelled on a monthly basis by using a mathematical programming (LP) formulation to find optimum cropping patterns, subject to land, water and downstream release constraints, and applied to the Cauvery basin. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analysed in the context of multiobjective planning and the trade-offs discussed.

Novel peptides of therapeutic promise from Indian Conidae

Highly structured small peptides are the major toxic constituents of the venom of cone snails, a family of widely distributed predatory marine molluscs. These animals use the venom for rapid prey immobilization. The peptide components in the venom target a wide variety of membrane-bound ion channels and receptors. Many have been found to be highly selective for a diverse range of mammalian ion channels and receptors associated with pain-signaling pathways. Their small size, structural stability, and target specificity make them attractive pharmacologic agents. A select number of laboratories mainly from the United States, Europe, Australia, Israel, and China have been engaged in intense drug discovery programs based on peptides from a few snail species. Coastal India has an estimated 20-30% of the known cone species; however, few serious studies have been reported so far. We have begun a comprehensive program for the identification and characterization of peptides from cone snails found in Indian Coastal waters. This presentation reviews our progress over the last 2 years. As expected from the evolutionary history of these venom components, our search has yielded novel peptides of therapeutic promise from the new species that we have studied.

Systems Analysis of Tank Irrigation: II. Delayed Start and Water Deficit

Tank irrigation systems in the semiarid regions of India are discussed in this paper. To optimize the grain yield of rice, it is essential to start the agricultural operations in the second week of July so that favorable climatic conditions will prevail during flowering and yield formation stages. Because of low inflow during the initial few weeks of the crop season, often farmers are forced to delay planting until sufficient sowing rain and inflow have occurred or to adopt deficit irrigation during this period. The delayed start affects the grain yield, but will lead to an improved irrigation efficiency. A delayed start of agricultural operations with increased irrigation efficiency leads to the energy resources becoming critical during the peak requirement week, particularly those of female labor and animal power. This necessitates augmenting these resources during weeks of their peak use, either by reorganizing the traditional methods of cultivation or by importing from outside the system.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Artificial neural networks and multicriterion analysis for sustainable irrigation planning

The objective of the present paper is to select the best compromise irrigation planning strategy for the case study of Jayakwadi irrigation project, Maharashtra, India. Four-phase methodology is employed. In phase 1, separate linear programming (LP) models are formulated for the three objectives, namely. net economic benefits, agricultural production and labour employment. In phase 2, nondominated (compromise) irrigation planning strategies are generated using the constraint method of multiobjective optimisation. In phase 3, Kohonen neural networks (KNN) based classification algorithm is employed to sort nondominated irrigation planning strategies into smaller groups. In phase 4, multicriterion analysis (MCA) technique, namely, Compromise Programming is applied to rank strategies obtained from phase 3. It is concluded that the above integrated methodology is effective for modeling multiobjective irrigation planning problems and the present approach can be extended to situations where number of irrigation planning strategies are even large in number. (c) 2004 Elsevier Ltd. All rights reserved.

An integrated model for optimal reservoir operation for irrigation of multiple crops

An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.

Cytochrome P4504f, a potential therapeutic target limiting neuroinflammation

Inflammatory processes are involved in the pathogenesis and/or progression of acute central nervous system (CNS) infection, traumatic brain injury and neurodegenerative disorders among others indicating the need for novel strategies to limit neuroinflammation. Eicosanoids including leukotrienes, particularly leukotriene B-4 (LTB4) are principle mediator(s) of inflammatory response, initiating and amplifying the generation of cytokines and chemokines. Cytochrome P450 (Cyp), a family of heme proteins mediate metabolism of xenobiotics and endogenous compounds, such as eicosanoids and leukotrienes. Cytochrome P4504F (Cyp4f) subfamily includes five functional enzymes in mouse. We cloned and expressed the mouse Cyp4f enzymes, assayed their relative expression in brain and examined their ability to hydroxylate the inflammatory cascade prompt LTB4 to its inactive 20-hydroxylated product. We then examined the role of Cyp4fs in regulating inflammatory response in vitro, in microglial cells and in vivo, in mouse brain using lipopolysacharide (LPS), as a model compound to generate inflammatory response. We demonstrate that mouse brain Cyp4fs are expressed ubiquitously in several cell types in the brain, including neurons and microglia, and modulate inflammatory response triggered by LPS, in vivo and in microglial cells, in vitro through metabolism of LTB4 to the inactive 20-hydroxy LTB4. Chemical inhibitor or shRNA to Cyp4fs enhance and inducer of Cyp4fs attenuates inflammatory response. Further, induction of Cyp4f expression lowers LTB4 levels and affords neuroprotection in microglial cells or mice exposed to LPS. Thus, catalytic activity of Cyp4fs is a novel target for modulating neuroinflammation through hydroxylation of LTB4. (C) 2011 Elsevier Inc. All rights reserved.

Modeling reservoir irrigation in uncertain hydrologic environment

In a detailed model for reservoir irrigation taking into account the soil moisture dynamics in the root zone of the crops, the data set for reservoir inflow and rainfall in the command will usually be of sufficient length to enable their variations to be described by probability distributions. However, the potential evapotranspiration of the crop itself depends on the characteristics of the crop and the reference evaporation, the quantification of both being associated with a high degree of uncertainty. The main purpose of this paper is to propose a mathematical programming model to determine the annual relative yield of crops and to determine its reliability, for a single reservoir meant for irrigation of multiple crops, incorporating variations in inflow, rainfall in the command area, and crop consumptive use. The inflow to the reservoir and rainfall in the reservoir command area are treated as random variables, whereas potential evapotranspiration is modeled as a fuzzy set. The model's application is illustrated with reference to an existing single-reservoir system in Southern India.

Integrated Reservoir Operation Modeling for Irrigation Systems - A Multi-Objective Approach

An integrated reservoir operation model is presented for developing effective operational policies for irrigation water management. In arid and semi-arid climates, owing to dynamic changes in the hydroclimatic conditions within a season, the fixed cropping pattern with conventional operating policies, may have considerable impact on the performance of the irrigation system and may affect the economics of the farming community. For optimal allocation of irrigation water in a season, development of effective mathematical models may guide the water managers in proper decision making and consequently help in reducing the adverse effects of water shortage and crop failure problems. This paper presents a multi-objective integrated reservoir operation model for multi-crop irrigation system. To solve the multi-objective model, a recent swarm intelligence technique, namely elitist-mutated multi-objective particle swarm optimisation (EM-MOPSO) has been used and applied to a case study in India. The method evolves effective strategies for irrigation crop planning and operation policies for a reservoir system, and thereby helps farming community in improving crop benefits and water resource usage in the reservoir command area.