Impact of Spatial Data Availability on Climate Change Prediction in the Weyib River Basin in Ethiopia

Impact of spatial data availability on the temperature and precipitation prediction characteristics of Weyib River basin in Ethiopia has been investigated using CMIP5-CanESM2 model for the RCP8.5, RCP4.5 and RCP2.6 scenarios. The objective of the present study is to characterize how future temperatures and precipitation prediction under CMIP5-CanESM2 model output varies against diverse averaged arbitrary spatial weather stations found in the basin. The statistical downscaling model tested and verified using the observed daily data for twelve, six and three averaged arbitrary spatial weather stations as well as for a single weather station was used to predict the future climate scenarios. The results revealed that the mean annual daily maximum and minimum temperature and precipitation for twelve, six and three arbitrary spatial stations have revealed an increasing trend in the upcoming periods until the end of the century. In single station analysis, the trend itself has changed from increasing trend to decreasing trend in case of maximum and minimum temperature. In case of precipitation, no visible trend has been observed in case of single station analysis. Therefore, the variation in amount and distribution of precipitation and temperature among the four averaged spatial stations in the same study area might affect the water resources and agriculture of the basin and also instead of using a single weather station to predict future climate variables for a particular study basin, it is more reliable using averages of numerous spatial weather stations data.     

An Optimization Approach for Assessing the Reliability of Rainwater Harvesting

This study was aimed at developing an optimization approach to rainwater harvesting (RWH) considering three (3) water consumption scenarios (WCS). These scenarios which include basic water need (BWN), pour flush (PF) and full plumbing connection (FPC) corresponding to 50 litres per capita per day (lpcd), 75(lpcd) and 150(lpcd) respectively were simulated for different categories of buildings. Reliability of supply was determined by first obtaining composite surplus/deficit of rainwater followed by optimizing the redistribution of surplus rainwater harvested to deficient buildings. Results showed that when total annual rainfall intercepted by roof exceeded total demand, 100% reliability of water supply was guaranteed. Reliability was found to be a linear function of storage. When reliability of supply is possible, the optimized storage bears an inverse exponential relationship to the roof plan area per capita. The relationship between surplus/deficit and roof plan area per capita follows a one-phase decay pattern. An optimal redistribution of surplus water from self-sufficient buildings to deficient ones gave an improvement in supply reliability from 64 to 87% for basic water need, 47 to 58% for pour flush and 28 to 29% for full plumbing connection.     

A Flood Forecasting Model that Considers the Impact of Hydraulic Projects by the Simulations of the Aggregate reservoir’s Retaining and Discharging

The hydraulic projects, such as reservoirs, ponds, and paddy fields, have a marked influence on the generation of floods, causing a number of difficulties where hydrological forecasting is concerned. To consider the influence of the hydraulic projects in hydrological forecasting, a modified TOPMODEL is presented in the paper, based on the simulation rules of the aggregate reservoir’s retaining and discharging (ARRD). In the new purposed model, termed as ARRD-TOPMODEL, the hydraulic projects are first aggregated as an equivalent reservoir, then the simulation rules of the aggregate reservoir’s retaining and discharging are determined, finally, the simulation rules are combined with an original TOPMODEL model calibrated using the floods not influenced by the hydraulic projects for flood forecasting. The ARRD-TOPMODEL was tested on the upstream of Wudaogou station basin in Northeast China. The results show that compared to the original model, the qualified rate (i.e., the ratio of the number of floods that meet acceptable criteria and the total number of floods) of runoff forecasting was increased from 73% to 100%. The problems that the overestimation of the runoff at beginning of flood season and after a long drought, as well as that the underestimation of the large flood in middle flood season are both solved, and the flood processes predicted by the new model are more consistent with the observed ones. All of these demonstrate that the newly developed model is superior to the original one and the simulation rules of the aggregate reservoir’s retaining and discharging are capable of accurately accounting for the influence of the hydraulic projects on the floods.     

Water Bloom Precursor Analysis Based on Two Direction S-Rough Set

In the field of water quality management, it is vital to determine the main precursory anomalies from the precursor of intricate water bloom in the context of a given area. In this paper, a water bloom precursor analysis method, based on two direction singular rough set, was proposed. This approach was produced on the basis of the different sections and pre-water bloom of water bloom precursor anomalies and characteristic of elements transferred in singular rough set. For testing the validity of two direction singular rough set application in water bloom precursor analysis, Xiangxi River, which is one of the typical tributaries of Three Gorges Reservoir in China, was selected as study area. The result showed that compared with other indexes, pH and dissolved oxygen (DO) are the most valuable indicators of water bloom in the precursory anomalies. Furthermore, regarding with water bloom precursory anomalies in Xiangxi River, most of the nutrient loading and biological community are the key indicators. Hence, this method can determine the main precursory anomaly for water bloom in the study area, which provides powerful knowledge support to water quality specialists for them to comprehensively analyze precursory anomaly so as to find out its relationship with occurrence law of water bloom.     

An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System,Support Vector Machine and Artificial Neural Network Models

Sediment transport in streams and rivers takes two forms as suspended load and bed load. Suspended load comprises sand + silt + clay-sized particles that are held in suspension due to the turbulence and will only settle when the stream velocity decreases, such as when the streambed becomes flatter, or the streamflow into a pond or lake. The sources of the suspended sediments are the sediments transported from the river basin by runoff or wind and the eroded sediments of the river bed and banks. Suspended-sediment load is a key indicator for assessing the effect of land use changes, water quality studies and engineering practices in watercourses. Measuring suspended sediment in streams is real sampling and the collection process is both complex and expensive. In recent years, artificial intelligence methods have been used as a predictor for hydrological phenomenon namely to estimate the amount of suspended sediment. In this paper the abilities of Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and Adaptive Network Based Fuzzy Inference System (ANFIS) models among the artificial intelligence methods have been investigated to estimate the suspended sediment load (SSL) in Ispir Bridge gauging station on Coruh River (station number: 2316). Coruh River is located in the northern east part of Turkey and it is one of the world”s the fastest, the deepest and the largest rivers of the Coruh Basin. In this study, in order to estimate the suspended sediment load, different combinations of the streamflow and the SSL were used as the model inputs. Its results accuracy was compared with the results of conventional correlation coefficient analysis between input and output variables and the best combination was identified. Finally, in order to predict SSL, the SVM, ANFIS and various ANNs models were used. The reliability of SVM, ANFIS and ANN models were determined based on performance criteria such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Efficiency Coefficient (EC) and Determination Coefficient (R²).     

Temporal Hydrologic Alterations Coupled with Climate Variability and Drought for Transboundary River Basins

Climate change (CC) and drought episode impacts linked with anthropogenic pressure have become an increasing concern for policy makers and water resources managers. The current research presents a comprehensive methodology but simple approach for predicting the annual streamflow alteration based on drought indices and hydrological alteration indicators. This has been achieved depending on the evaluation of drought severity and CC impacts during the human intervention periods to separate the influence of climatic abnormality and measure the hydrologic deviations as a result of streamflow regulation configurations. As a representative case study, the Lesser Zab River Basin in northern Iraq has been chosen. In order to analyse the natural flow regime, 34 hydrological years of streamflow (1931–1965) prior to the main dam construction were assessed. The Indicators of Hydrologic Alteration (IHA) method has been applied to quantify the hydrological alterations of various flow characteristics. In addition, an easy approach for hydrological drought prediction in relatively small basins grounded on meteorological parameters during the early months of the hydrological year has been presented. The prediction was accomplished by implementing the one-dimensional drought examination and the reconnaissance drought index (RDI) for evaluating the severity of meteorological drought. The proposed methodology is founded on linear regression relations connecting the RDI of 3, 6, and 12 months and the streamflow drought index (SDI). The results are critical for circumstances where an early exploration of meteorological drought is obtainable. Outcomes assist water resources managers, engineers, policy makers and decision-makers responsible for mitigating the effects of CC.     

Analysis of the Spatial Characteristics of the Water Usage Patterns Based on ESDA-GIS: An Example of Hubei Province,China

The spatial characteristics and the high-duty water regions of the Water Usage Patterns (WUP) are very important for the allocation and management of water resources. Taken Hubei province, China as an example, we adopted the exploratory spatial data analysis (ESDA) method to investigate the spatial dependence and local patterns of the WUP from 2003 to 2012. Subsequently, the spatial variation mechanisms were analyzed through the gravity center model. The results indicated that the overall spatial dependence of the agricultural WUP was detected (more significant after 2008). Moreover, the global spatial autocorrelation analysis results on the domestic WUP showed statistical significance (Moran’s I?>?0.1, P?<?0.05). These indicated that the local patterns were presented. The high values clustering areas of the agricultural and domestic WUP were mainly distributed in the central province and in the western province respectively. However, the approximate random distribution was identified for the industrial WUP because the industrial development had been conducted widely in the whole province during these years. Furthermore, the governmental policies and natural environment contributed to the spatial evolution tendency of the WUP. An increasing trend of the spatial association of the agricultural WUP and a significant decreasing trend of that of the domestic WUP, which suggested that the natural circumstance superiority and the industrial structure adjustment related to water utilization has been utilized and implemented effectively. This study can provide a useful reference and guidance for scientific planning of water resource systems.     

Reliability Analysis Applied on Land Subsidence Effects of Groundwater Remediation: Probabilistic vs. Deterministic Approach

The quantification of soil variability is one of the most important aspects in the geo-engineering context. The uncertainty analysis is the main part of the reliability assessment for which a quantitative evaluation was performed in this study. The Reliability Index and the Probability of Failure using the First-Order Reliability Method (FORM) represents both, an effective method which is easy to implement at the same time. This work analyzes possible effects of compaction induced into the aquifer of the Scarlino Plain, caused by the extension of the hydraulic barrier for groundwater remediation. The currently implemented vertical barrier is composed of 12 wells which reach the depth of 10 m. The improvement of the project involves the construction of a further 40 clusters, each consisting of a doublet which intercepts different depths (10 and 18 m). The models of the subsoil stratigraphy and of the groundwater were built using a numerical model. The groundwater flow and the piezometric surface in the current configuration of the barrier were studied and the project configuration was evaluated. Using the Aquitard drainage model, the land subsidence was estimated to calculate the maximum admissible displacement related to exhibited goods, the so called territorial vulnerability. The evaluation analysis was performed using a traditional deterministic approach, followed by a reliability method based on probabilistic models. Finally, the respective results were reported in a soil mapping with overlapping layers.     

Modeling River Mixing Mechanism Using Data Driven Model

Modeling river mixing mechanism in terms of pollution transmission in rivers is an important subject in environmental studies. Dispersion coefficient is an important parameter in river mixing problem. In this study, to model and predict the longitudinal dispersion coefficient (D _L ) in natural streams, two soft computing techniques including multivariate adaptive regression splines (MARS) as a new approach to study hydrologic phenomena and multi-layer perceptron neural network as a common type of neural network model were prepared. To this end, related dataset were collected from literature and used for developing them. Performance of MARS model was compared with MLP and the empirical formula was proposed to calculate D _L . To define the most effective parameters on D _L structure of obtained formula from MARS model and more accurate formula was evaluated. Calculation of error indices including coefficient of determination (R²) and root mean square error (RMSE) for the results of MARS model showed that MARS model with R²?=?0.98 and RMSE?=?0.89 in testing stage has suitable performance for modeling D _L . Comparing the performance of empirical formulas, ANN and MARS showed that MARS model is more accurate compared to others. Attention to the structure of developed MARS and the most accurate empirical formulas model showed that flow velocity, depth of flow (H) and shear velocity are the most influential parameters on D _L .     

Overview of Water Policy Developments: Pre- and Post-2015 Development Agenda

The year 2015 marked the end of some important universal decisions regarding water developments. The International Decade for Action ‘Water for Life’ (2005–2015) was concluded so that a “Post-2015 Development Agenda” is now defined. 2015 was also the year when UN Millenium Goals (MDGs) came to an end to convert into the new Agenda, which is a process led by the United Nations (UN) to define the future global development framework. The proposed goal is now referred to as SDG’s or Sustainable Development Goals, that extend existing commitments such as the MDGs and the priorities of Rio + 20. SDG’s will balance the economic, social and environmental dimensions of sustainable development with a strong linkage between environment and socio-economic goals. They converge with the post-2015 development agenda, now called Agenda 30 as these goals will be valid until 2030. One of the major concepts of SDG’s is water security, which is the basic element of the Global Goal on Water. Water security is the capacity of a population to safeguard sustainable access to adequate quantities of acceptable quality of water for sustaining livelihoods, human well-being, and socioeconomic development, for ensuring protection against pollution and waterrelated disasters, and for preserving ecosystems in a climate of peace and political stability. This paper discusses the developments in water management within the last 30 years, which eventually led to the above concepts. A summary is provided on key events and documents of these past years to point out how the international community has reacted towards present and emerging needs of the society.