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Surveys were undertaken for characterization and evaluation of genetic diversity of Jamun (SyzygiumcuminiiSkeels) of seedling origin for different morphological characters of tree characters and leaf characters during 2016-17 and 2017-18 in the Jamun growing in Northern Bastar Plateau region of Chhattisgarh areas. Investigations were undertaken during the entire vegetative phase to assess the distribution, range and to record the range of genetic variability of different morphological traits on the selected sixty trees. Mature leaves were plucked and analyzed for different parameters such as leaf surface and leaf glands. Results of evaluated Jamun genotypes showed wide variability for studied characteristic.

PurposeThe purpose of this study is to investigate the effect of various heat conditions on the durability of eggshell powder (ESP)–flyash (FA) geopolymer subjected to wetting–drying cycles.Design/methodology/approachIn this study, two waste materials, ESP and FA, which are destined for landfills, were used as precursors to produce geopolymers in a sustainable manner. The mixture of Na2SiO3and NaOH was used as a liquid alkaline activator in geopolymerization. The ESP and FA content were varied as 30, 50 and 70% and Na2SiO3/NaOH ratios were varied as 0.5, 1 and 2. Geopolymer samples were cured at three heat conditions: 25°C (ambient temperature), 50°C and 80°C for seven days prior to durability tests.FindingsThe results of this study revealed that the strength loss of the geopolymer decreases with an increase in curing temperature up to 50°C and then increases for higher temperature up to 80°C. Further, the strength loss of the geopolymer decreases with an increase in FA replacement and Na2SiO3/NaOH ratio. Geopolymer composites exhibited early strength development because of the inclusion of calcium-rich ESP. The weight loss of the ESP–FA geopolymer follows a similar pattern of strength loss. Geopolymer samples previously cured at optimum heat condition of 50°C for seven days exhibited higher durability.Originality/valueThe inclusion of calcium-rich ESP in FA-based geopolymer is novel research. As ESP–FA geopolymer composites show higher mechanical strength and higher durability compared to Indian standards, the potential use of this geopolymer can be in road subbases/subgrades.

The Soil Conservation Service Curve Number (SCS-CN) method is frequently used for the estimation of direct surface runoff depth from the small watersheds. Coupling the SCS-CN method with the Soil Moisture Balance (SMB) method, new simple 2-parameters rainfall-runoff model and 3-parametrs rainfall-sediment yield models are derived for computation of runoff and sediment yield respectively. The proposed runoff (R2) and sediment yield (S2) models have been tested on a large set of rainfall-runoff and sediment yield data (98 storm events) obtained from twelve watersheds from different land use/land cover, soil and climatic conditions. The improved runoff (R2) and sediment yield (S2) models show superior results as compared to the existing Mishra et al. (S1) and original SCS-CN (R1) models. The results and analysis justify the use of the proposed models for field applications.

The sediment graph models are useful for computation of sediment yield as well as total sediment out flow from watershed. In this study, the analytical development of proposed sediment graph models is based on Soil Moisture Accounting (SMA) procedure coupled Soil Conservation Service-Curve Number (SCS-CN) method, Nash’s Instantaneous Unit Sediment Graph (IUSG)model and Power law. This coupling has led to the development of four sediment graph models (SGMs), i.e., SMA-SGM1, SMA-SGM2, SMA-SGM-3 and SMA-SGM4 depending on the four different hydrologic conditions as: (i) initial soil moisture ( V 0 ) = 0 and initial abstraction ( I a ) = 0, (ii) initial soil moisture ( V 0 ) ≠ 0 a n d i n i t i a l a b s t r a c t i o n I a = 0 , (iii) initial soil moisture ( V 0 ) = 0 a n d ( I a ) ≠ 0 , and (iv) initial soil moisture ( V 0 ) ≠ 0 a n d i n i t i a l a b s t r a t i o n ( I a ) ≠ 0 , respectively. These models are applied on six natural watersheds with nineteen storm events having different land use/land cover, climatic condition (arid, semi-arid, humid and sub-tropical), rainfall and land slope conditions. The goodness-of-fit statistics is evaluated in terms of Nash Sutcliffe efficiency (NSE) and relative error (RE) between observed and simulated (calibrated and validated) sediment graphs. Further, the performance of these models is also compared with the sediment graph model of Bhunya et al. (2010) (BSGM) on all the six study watersheds. It is found that the proposed models perform very well in simulating sediment yield generation process for all the watersheds and show significant improvement over the BSGM model.

In this research, the application of eggshell powder (ESP) and flyash (FA) as calcium oxide and alumino-siliceous precursors to produce a feasible geopolymer for pavement construction was studied. Effect of heat curing on long-term mechanical strength development of the geopolymer was also evaluated. The ESP is a waste-by-product produced from crushing waste eggshells, whilst FA is a waste-by-product generated from the coal-fired electricity production plant. Geopolymer composites were produced using three activator ratios Na2SiO3/NaOH − 0.5, 1.0, and 2.0 with a fixed 10 M concentration of NaOH. The curing process was done at 50 °C and 80 °C temperatures for 7 days, 28 days, and 56 days. The optimum activator content (OAC) providing the maximum dry unit weight (MDU) was found to increase with an increment in activator ratio and FA replacement ratio. Na2SiO3/NaOH − 2.0 was found as an optimum activator ratio providing the highest unconfined compressive strength (UCS) and the highest split tensile strength (STS). Similarly, optimum precursor ratio providing the highest UCS followed by highest STS was found as ESP50:FA50. Microstructural analysis showed that cementitious products were formed for the ESP-FA geopolymer at the optimum activator ratio and heat conditions.

Summary The increasing population and large scale growth with the development of modern science and technology has indicated very high stress on water sector in Rajasthan in India. Availability of water and uniformity of rainfall distribution is changing day by day due to shifting of monsoon in Rajasthan. The spatial and temporal variations in the rainfall in different river basins in Rajasthan are drastic due to which flood situation arises in the tributaries of Chambal river basin every year. Simultaneously on the other hand drought situation arises in the other different places in the most of the river basins which are also under dark zone. In totality natural water resources are also limited in Rajasthan so there is an urgent need for its proper planning, development and management of the available water duly taking care of environmental, ecological, socio-economic aspects and their inter-relationships. Annual surplus water of about 1437 MCM in the river Chambal is going waste and ultimately reaches to sea after creating flood situations in various places in India including Rajasthan, while on the other hand 1077 MCM water is a requirement in the four other basins in Rajasthan i.e. Banas, Banganga, Gambhir and Parbati at 75% dependability. Interlinking and water transfer from Chambal to these four river basins is the prime solution for which 372 km link channel including 9 km tunnel of design capacity of 300 cumec with 64 m lift is required.

Enormous cost and manpower utilization encountered in constructing a water resource project demands a great deal of attention in devising precise Rainfall-Runoff models for its successful performance. These models are dependent on the physiographic, climatic and biotic characteristics of the basin. These factors sometimes induce either a linear, non-linear or highly complex behaviour among the rainfall and runoff parameters. The unstructured nature of Rainfall-Runoff relations has diverted the attention of researchers towards Soft Computing tools which, harnesses reasoning, intuition, consciousness and wisdom possessed by human beings. Soft Computing being a multi-disciplinary field uses a variety of statistical, probabilistic and optimization tools which complement each other to produce its three main branches viz., Neural Networks, Genetic Algorithms and Fuzzy Logic. These techniques, whether complementing each other or working on their own, are able to model complex or unknown relationships which are either nonlinear or noisy. The review paper presents an introduction to these techniques and discusses their applications in modelling Rainfall-Runoff relations which to some extent have replaced time consuming conventional mathematical techniques with wiser and time saving computing tools.

Transformation of occurred rainfall into runoff generated within a catchment is a complex natural phenomenon that passes through various inter-related processes and influenced by many topographic, geographic, geologic and sociologic factors. To develop a model that can reliably imbibe the complex Rainfall-Runoff interaction, two different approaches namely, conventional regression and Artificial Neural Networks (ANN) have been attempted for Rajsamand Catchment located in the Banas River Basin of Rajasthan. The monthly weighted rainfall of the catchment and inflow received during the monsoon period in the Rajsamand Dam for last twenty years were used for the study. The weighted rainfall and corresponding runoff for the months July, August, September and the monsoon period were considered as inputs and outputs respectively for the model. The performance compared using three different statistical metrics reveal that, the Rainfall-Runoff Model based on ANN approach offer better prediction accuracy than the conventional regression model.