நீரியல்: தற்போதைய ஆராய்ச்சி

A mechanism is presented explaining how mega meltwater avalanches could be generated on the surface of a continental ice sheet. It is shown that during periods of excessive climatic warmth when the continental ice sheet surface was melting at an accelerated rate, self-amplifying, translating waves of glacial meltwater emerge as a distinct mechanism of meltwater transport. It is shown that such glacier waves would have been capable of attaining kinetic energies per kilometer of wave front equivalent to 12 million tons of TNT, to have achieved heights of 100 to 300 meters, and forward velocities as great as 900 km/hr. Glacier waves would not have been restricted to a particular locale, but could have been produced wherever continental ice sheets were present. Catastrophic floods produced by waves of such size and kinetic energy would be able to account for the character of the permafrost deposits found in Alaska and Siberia, flood features and numerous drumlin field formations seen in North America, and many of the lignite deposits found in Europe, Siberia, and North America. They also could account for how continental debris was transported thousands of kilometers into the mid North Atlantic to form Heinrich layers. It is proposed that such layers’ form at times when a North Atlantic sea ice shelf borders the ice sheet and when climate warms abruptly producing accelerated meltwater discharge.

Land cover and Climate change are very important issues in terms of global context and their responses to environmental and socio-economic drivers. The dynamic of these two factors is currently affecting the environment in unbalanced way including watershed hydrology. In this paper the impact of land use/cover change on stream flow particularly on low flow were evaluated through application of the model Soil and Water Assessment Tool (SWAT) in Gumara watershed, Upper Blue Nile basin Ethiopia. The land use/cover data were obtained from Land Sat image and processed by ERDAS IMAGINE 2010 software. Three land use land cover data; 1973, 1986, and 2013 were prepared and these data were used for base map, model calibration and change study respectively. So, as to evaluate the effect of land use/cover change on low flow of the catchment, the stream flow was simulated by changing 1973 and 2013 LULC but the climate data, which is 1973-1982, was used and it was constant. The low flow of the catchment for these two decades was extracted in simulated flows by Seven Day Sustained (SDS) low flow separation method. The model (SWAT) was calibrated by 1986-1991 climate data and 1986 land use land cover data by using 11 important model parameters selected by sensitivity analysis. The consistency of values of those calibrated parameters was also validated by 1992-1995 climates and with the same land use land cover data. Based on the result, the extreme low flow of Gumara watershed has been decreasing from 0.53 m3/s to 0.43 m3/s which showed decreasing by 0.1 m3/s that is 18.87%. From the overall results of the study, it is possible to conclude that land use land cover change has been influencing the low flow or dry season flow of the catchment. This study has been designed to show how much the land use/cover has been changed and affects the low flow or dry season environmental flow of the catchment. The result has showed some indications that there has to be restoration activities on the land use cover nature of the study area.

Many techniques, approaches and tools were used in this Research to achieve the Methodology. Using artificial neural network to simultaneous hydraulic parameters is one of these techniques. Transmissivity and storativity consider the most important parameter in each aquifer due to the reality of their effect on the aquifer properties. In this research, it is assumed that the transmissivity (T) and the storativity (S), represented by coordinates (X), (Y), hydraulic head (H), and observation times (t). These variables were chosen depending on the literature review. In the present study, the hydraulic head values at each cell (H) and the location of the cells (x, y) are considered as input parameters for finding the unknown parameters. The transmissivity (T) and storativity values (S) at cells are assumed and used in the finite difference method (Forward model) in order to find the value of hydraulic head at that cell. The hydraulic head values were used in the artificial neural networks (Inverse model) to estimate transmissivity (T) and storativity values (S) for Wadi El Natrun Depression. The study is based on coupling of forward model and inverse model. In general, the parameter estimation process consists of identifying a model that would reverse a complex forward relation.

Sediment yield in the Upper Tana Basin in Kenya has implications on the sustainability of Hydro-Electric Power (HEP) dams and water resources development projects. Therefore, a study was undertaken in the basin to establish the extent to which rainfall and river discharges influence the sediment yield in the catchment. The study was based on hydrological data obtained from the Water Resources Management Authority (WARMA) and Kenya Meteorological Department (KMD). The river discharge data was obtained from three RGS Maragua (4BE01), Gura (4AD01) and Tana Sagana (4BC02) and rainfall data was obtained from Sagana Fish Farm and Nyeri Ministry of Works for the of period 1960-2013.The study also applied the Soil Water Assessment Tool (SWAT) Model to determine the extent to which the model can be used to simulate streamflow and sediment yield in the basin. The results of the study showed that there is a significant variability in streamflow and sediment yield in the Upper Tana Basin. In the period between 1960 and 2015, the mean total annual river discharge of Tana Sagana was 128 m3s-1, and the maximum and minimum river discharges were 29.94 m3s-1 and 3.15 m3s-1, respectively. There was an indication of increasing trend in rainfall and subsequently sediment yield in the basin, which may be attributed to alteration of land use and climatic change. The results showed that SWAT model was quite good in simulating the variability of river discharge. The analysis revealed a poor relationship between sediment yield and rainfall. However, the relationship between rainfall and stream flow was strong with r value of 0.9 which is significant at p=0.05. Relationship between simulated and observed river discharge had a R2 of 0.442, r of 0.665 and NSE of -89.43. The relationship between simulated and observed sediment yield had a R2 of 0.733, r of 0.86 and NSE of 0.69. The results of this study showed that SWAT model can be used to predict sediment yield in the Upper Tana catchment. The model had good performance when daily rainfall, stream flow and sediment yield data were used. Thus, the model can be used to establish the relationship between rainfall, discharge, and sediment yield in a highly human-impacted tropical catchment area. The study puts also forward various recommendations on land and water resources management in the basin.

Eight Tef varieties including local checks were evaluated with the objective of selecting adaptable, best performing varieties and to assess farmers’ criteria for Tef variety selection during 2008 and 2009 cropping season at Areka and Hossana stations of Areka Agricultural Research center in the Southern region of Ethiopia. In the study the Tef varieties namely Koye, Gimbichu, Quncho, Dega Tef, Keytena, Amarach and Ajora-1 were collected from the Federal and regional Research center along with local checks, Ethiopia, and Regional Agricultural Research Institute. These materials were put into trial at Areka Agricultural Research center station farms at Areka and Hossana of Wolayta and Hadiya Zones. The trial was laid out in a randomized complete block design with three replications. Each plot measured 3 m × 3 m with 1 m between plots and 1.5 m between blocks. Sowing was done within the last week of July to 1st week of August 2008 and 2009. Data on various characters, such as plant height, panicle length, days to heading, and days to maturity and grain yield. Data was subjected to analysis of variance and there was highly significant difference (p<0.01) among the varieties for grain yield and some of agronomic traits. The results for the trials indicated that there were significant yield differences between the local check and the released varieties at two stations. At Areka, the combined analysis of variance over years indicated that varieties Koye, Amarch and Quncho gave the highest grain yield viz., 988.7, 984.3 and 958.7 kg/ha respectively. Similarly, at Hosanna, varieties Gimbichu, Quncho and koye out yielded other varieties and had yield advantage of 31.9, 25.14 and 15.14% over local variety, respectively. Both combined across locations over year’s analysis and farmers’ assessments identified two varieties Quncho and Koye as potential varieties for wider production. This result also indicated that farmers were as capable as Researchers in varietal choice. Therefore, based on objectively measured traits (grain yield, days to maturity, plant height, panicle length, days to heading and farmers’ preference, Koye and Quncho are recommended for wider cultivation in Areka and Hossana areas of south Ethiopia while varieties (Amarach and Gimbichu) showed specific adaptability for Areka and Hossana areas respectively.

The SWAT model was used to estimate the runoff and sediment yield of Lolab watershed. The model was calibrated, validated, and assessed for evaluation to model ambiguity using Nash–Sutcliffe coefficient (NSE) and coefficient of determination (R2). Ten highly sensitive parameters were recognized for stream flow simulation of which CN2 (Initial SCS CN II value) factor was the most sensitive one and four highly sensitive parameters were recognized for sediment yield simulation of which SPCON (Linear parameters for sediment re-entrainment) was most sensitive one. The model was calibrated for a time period between 1993 to 2000 and validated from 2001 to 2004 for flow and sediment yield. The predicted and observed stream flow and sediment yields generally matched well. The results of the model calibration and validation showed reliable estimates of monthly stream flow (R2=0.74 and ENS=0.68) and yearly stream flow (R2=0.90 and ENS=0.68) during the calibration period and monthly stream-flow (R2=0.85 and ENS=0.83) and yearly stream-flow (R2=0.99 and ENS=0.91) during the validation period. For sediment yield, this study shows antremendous model efficiency of monthly sediment yield (R2=0.80 and ENS=0.79) and yearly sediment yield (R2=0.86 and ENS=0.78) during the calibration period and monthly sediment yield (R2=0.88 and ENS=0.86) and yearly sediment yield (R2=0.83 and ENS=0.58) during the validation period. This study showed that the SWAT model is competent of predicting sediment yields and hence can be used as a tool for water resources planning and management in the study watershed.

Chickpea is one of the grain food legumes contributing an enormous amount of protein to the human diet in Southern Ethiopia. Though a lot of improved varieties were released by research centers farmers depend on low yield and local varieties. Hence, participatory variety selection is one of the methods used to evaluate varieties through involvement of users. Participatory Variety Selection (PVS) were conducted during 2015/2016 in Mirab Badwacho and Damot Fullasa districts of South region, Ethiopia to assess the performance of chickpea (Cicer arietinum L.) varieties and to evaluate farmers’ selection criteria for chickpea. Six improved varieties with local check were laid out in a randomized complete block design with four replications. Significant variation among chickpea varieties were observed for most the agronomic traits collected except for number of pod per plant which was not significant. Concerning location, the majority of the traits were showed significant difference indicating dissimilarity in agro ecologies of the two districts. The study also revealed that in some cases the researchers’ selection match with farmers’ preferences. However, in general farmers have shown their own way of selecting a variety for their localities. These parameters include earliness, diseases and pest resistance, seed colour, branch number and length and seed size. Hence, including farmers’ preferences in a variety selection process is a paramount important. Therefore, based on attentively measured parameters, farmers’ favourites and the agro ecologies of the site the varieties Natoli, Dalota and Arerti are selected for the area. The varieties Habru and Ejere should also be given due consideration by farmers for its earlier maturity in the study area.