Search results for: sub-basin

Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

Abstract:

In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

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Authors: Elias Jemal Abdella

Abstract:

The Blue Nile River is an important shared resource of Ethiopia, Sudan and also, because it is the major contributor of water to the main Nile River, Egypt. Despite the potential benefits of regional cooperation and integrated joint basin management, all three countries continue to pursue unilateral plans for development. Besides, there is great uncertainty about the likely impacts of climate change in water availability for existing as well as proposed irrigation and hydropower projects in the Blue Nile Basin. The main objective of this study is to quantitatively assess the impact of climate change on the hydrological regime of the upper Blue Nile basin, western Ethiopia. Three models were combined, a dynamic Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model (RCM) that is used to determine climate projections for the Upper Blue Nile basin for Representative Concentration Pathways (RCPs) 4.5 and 8.5 greenhouse gas emissions scenarios for the period 2021-2050. The outputs generated from multimodel ensemble of four (4) CORDEX-RCMs (i.e., rainfall and temperature) were used as input to a Soil and Water Assessment Tool (SWAT) hydrological model which was setup, calibrated and validated with observed climate and hydrological data. The outputs from the SWAT model (i.e., projections in river flow) were used as input to a Water Evaluation and Planning (WEAP) water resources model which was used to determine the water resources implications of the changes in climate. The WEAP model was set-up to simulate three development scenarios. Current Development scenario was the existing water resource development situation, Medium-term Development scenario was planned water resource development that is expected to be commissioned (i.e. before 2025) and Long-term full Development scenario were all planned water resource development likely to be commissioned (i.e. before 2050). The projected change of mean annual temperature for period (2021 – 2050) in most of the basin are warmer than the baseline (1982 -2005) average in the range of 1 to 1.4oC, implying that an increase in evapotranspiration loss. Subbasins which already distressed from drought may endure to face even greater challenges in the future. Projected mean annual precipitation varies from subbasin to subbasin; in the Eastern, North Eastern and South western highland of the basin a likely increase of mean annual precipitation up to 7% whereas in the western lowland part of the basin mean annual precipitation projected to decrease by 3%. The water use simulation indicates that currently irrigation demand in the basin is 1.29 Bm3y-1 for 122,765 ha of irrigation area. By 2025, with new schemes being developed, irrigation demand is estimated to increase to 2.5 Bm3y-1 for 277,779 ha. By 2050, irrigation demand in the basin is estimated to increase to 3.4 Bm3y-1 for 372,779 ha. The hydropower generation simulation indicates that 98 % of hydroelectricity potential could be produced if all planned dams are constructed.

Keywords: Blue Nile River, climate change, hydropower, SWAT, WEAP

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Authors: Can Liu, Graham Markowitz, John Balay, Ben Pratt

Abstract:

Baseline or natural hydrology is commonly employed for hydrologic modeling and quantification of hydrologic alteration due to manmade activities. It can inform planning and policy related efforts for various state and federal water resource agencies to restore natural streamflow flow regimes. A common challenge faced by hydrologists is how to replicate unaltered streamflow conditions, particularly in large watershed settings prone to development and regulation. Three different methods were employed to estimate baseline streamflow conditions for 6 major subbasins the Susquehanna River Basin; those being: 1) incorporation of consumptive water use and reservoir operations back into regulated gaged records; 2) using a map correlation method and flow duration (exceedance probability) regression equations; 3) extending the pre-regulation streamflow records based on the relationship between concurrent streamflows at unregulated and regulated gage locations. Parallel analyses were perform among the three methods and limitations associated with each are presented. Results from these analyses indicate that generating baseline streamflow records at large-scale watersheds remain challenging, even with long-term continuous stream gage records available.

Keywords: baseline hydrology, streamflow gage, subbasin, regression

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Authors: Abouchouaib Belahmira, Joerg W. Schneider, Hafid Saber, Sara Akboub

Abstract:

The lithofacies analyzed herein were reported from the interbedded fluvial and lacustrine deposits of the Oued Issene and El Menizla formations. These formations are part of the sedimentary fill of the Carboniferous (Stephanian) submontaneous Souss basin. The latter is situated in the western High Atlas Mountains, south-central Morocco, about 50km east of Agadir. The Souss basin started as a single basin but was separated into sub-basins called Ida Ou Zal and Ida Ou Ziki by sinistral displacement along the west branch of the Tizi N'Test Fault during the end of the Mauritanid phase of the Variscan orogeny in Morocco, after the early Stephanian (Kasimovian) and before the late middle Permian (Capitanian). The studied succession is a monotonous finning-upward sequence of 1800 m thick. It consists of fine-grained sandstone, finely bedded siltstone and thinly laminated claystone, and black shale. Herein we provide a detailed characterization of lithofacies of the upper El Menizla and Oued Issène formations, with a focus on the prevailing overbank to flood plain fine-grained lithofacies. The studied facies are capping the Stephanian alluvial fan basal clast-supported conglomerates that are intercalated bedded coarse-grained sandstones of Ikhourba Formation in the Ou Zal subbasin and Tajgaline Formation in the Ida Ou Ziki subbasin, respectively. Within the fluvial elements, only two main facies have been observed. It comprises channel-fill and channel-bar deposits, mostly occur as lenticular –shape sand bodies or sheet-like sand greenish to gray fine-to medium (Fm), massive internally structureless, or very locally exhibits a medium to large scale trough-cross bedding medium to coarse sandstone (St), observable in relatively thicker bed. These facies are laterally extensive, with a thickness varying from a few to several meters. Finer-grained sediments such as mud can be present as drapes over bedforms. Whilst the fluvial association FA1, the overbank elements are represented by a relatively wide range of 5 facies. This exhibit mostly a cm scale horizontally bedded greenish fine- to medium sand and silt, and mm scale fossiliferous thinly laminated dark gray- black Corganic-rich clays to siltstone associated with black shale. Thus, FA2 includes flood plain fines (Fh, R) associated with the paleosols and back swamp coaly clay facies (C). The floodplain lake element comprises only laminated organic-rich dark gray facies of claystone, black shale, and graded siltstone. Bedsets are dm to several meters thick (typically < 1 m thick). They are intercalated between several m-thick fluvial sandstone, extend over a few meters, and are poorly bioturbated. The lacustrine facies described in this study have been divided into two sub-facies (Fl, B) based on field observations that indicate differing environmental conditions of formation. Thus, the thorough analysis of the lithofacies of the Souss basin units allows us to reconstruct the original environment that was interpreted as a typical fluvial-dominated braided to anastomosing wide distributary channel system and surrounding deep to shallow freshwater floodplain lakes and back swamps.

Keywords: Souss, carboniferous, facies, depositional setting

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Authors: Ahmad Saadiq, Neeraj Sahu

Abstract:

Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

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