Climate change impacts on hydrology and water resources of the Upper Blue Nile River Basin, Ethiopia

Climate change / Hydrology / River basins / Runoff / Precipitation / Models / Dams / Operating policies / Water power / Drought / Analysis / Africa / Ethiopia / Egypt / Sudan / Upper Blue Nile River Basin

Water Resources Management Under Competing Demands in the Walawe River Basin, Sri Lanka

Many developing countries depend on their agricultural production to ensure food security. However, along with agriculture, there are many other sectors that impose demands on basin water resources. Declining water supplies and growing demands require better management decisions in water allocation. This paper describes the current water demand and supply situation in a rural river basin of a developing country and analyzes several solutions to overcome the water allocation issues

Modeling of multicomponent organic chemicaltransport in three phase porous media

A two-dimensional finite-element model was developed to predict coupled transient flow and multicomponent transport of organic chemicals which can partition between nonaqueous phase liquid, water, gas and solid phases in porous media under the assumption of local chemical equilibrium. Gas-phase pressure gradients are assumed negligible and liquid flow equations are solved simultaneously using an upstream weighted solution method with time-lagged interphase mass-transfer terms and phase densities. Phase-summed component transport equations are solved serially after computation of the velocity field also by an upstream weighted finite-element method. Mass-transfer rates are evaluated from individual phase transport equations by back-substitution and corrected for mass-balance errors. A number of hypothetical one- and two-dimensional simulations were performed to evaluate the applicability of the model to predict the transport of slightly soluble and volatile organics in three-fluid-phase porous media. Results indicate that mass-transfer rate and fluid density updating have negligible effects during periods of highly transient nonaqueous liquid phase migration but become important for long-term simulations as cumulative dissolution to the water phase and volatilization to the gas phase account for longer proportions of the total mass. Due to low solubilities of environmentally important organic liquids, the efficiency of organic removal by aqueous-phase dissolution and transport can be very slow. Gas-phase diffusion can have a significant influence on the mass transport of organics with large Henry\u27s constants

Modular neural network to predict the distribution of nitrate in ground water using on-ground nitrogen loading and recharge data

Artificial neural networks have proven to be an attractive mathematical tool to represent complex relationships in many branches of hydrology. Due to this attractive feature, neural networks are increasingly being applied in subsurface modeling where intricate physical processes and lack of detailed field data prevail. In this paper, a methodology using modular neural networks (MNN) is proposed to simulate the nitrate concentrations in an agriculture-dominated aquifer. The methodology relies on geographic information system (GIS) tools in the preparation and processing of the MNN input–output data. The basic premise followed in developing the MNN input–output response patterns is to designate the optimal radius of a specified circular-buffered zone centered by the nitrate receptor so that the input parameters at the upgradient areas correlate with nitrate concentrations in ground water. A three-step approach that integrates the on-ground nitrogen loadings, soil nitrogen dynamics, and fate and transport in ground water is described and the critical parameters to predict nitrate concentration using MNN are selected. The sensitivity of MNN performance to different MNN architecture is assessed. The applicability of MNN is considered for the Sumas-Blaine aquifer of Washington State using two scenarios corresponding to current land use practices and a proposed protection alternative. The results of MNN are further analyzed and compared to those obtained from a physically-based fate and transport model to evaluate the overall applicability of MNN

Estimating drought conditions using an ET-based drought index

Many operational drought indices focus on precipitation and temperature when depicting hydro-climatic anomalies and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between wet environmental evaporation which is the ET rate of a surface with unlimited moisture and actual ET is leveraged in a new drought index based on complementary relationship. The proposed drought index, the Evapotranspiration Water deficit Drought Index (EWDI), is to compare the ET rate of a saturated surface with current water demand. To calculate EWDI, monthly actual ET estimated from an improved GG model using precipitation, Normalized Difference Vegetation Index, and meteorological data. We presented that EWDI produces results that are consistent with the United States Drought Monitor which is widely used for drought monitoring. Also, we found that EWDI can serve as an indicator of rapidly evolving fast droughts developing over a few weeks and is able to capture drought conditions better when we use an accurate ET method

An Advanced Evapotranspiration Method and Application

Estimating evapotranspiration is an important component in the monitoring of agricultural and environmental systems. This chapter will focus on the developing evapotranspiration method using general meteorological data and Normalized Difference Vegetation Index (NDVI). The proposed model in this chapter will be refined by using both the complementary relationship and the Budyko framework. The relative evaporation parameter in the complementary relationship will be derived by using precipitation, potential evapotranspiration, and NDVI based on that the Budyko framework can support the complementary relationship. It is also important to determine whether the proposed model can compete and deliver accuracy similar to remote sending method in the aspect of application. The results in the first phase showed the proposed model could be a powerful methodology to estimate ET among the ground-based method. In the second phase, a nonlinear correction function was proposed to better describe the complementary relationship. We will also demonstrate that the use of ET is a better approach for drought estimations than considering reference ET. More importantly, the advantage of the proposed model is that it can comprehensively consider both effects of precipitation and vegetation information. Taken together, this chapter has extended our knowledge of ET to support water resource management

Integrated modeling of nitrate contamination of groundwater in agriculture-dominated watersheds

This paper presents and implements a framework for modeling the impact of land use practices and protection alternatives on nitrate pollution of groundwater in agricultural watersheds. The framework utilizes the national land cover database (NLCD) of the United State Geological Survey (USGS) grid and a geographic information system (GIS) to account for the spatial distribution of on-ground nitrogen sources and corresponding loadings. The framework employs a soil nitrogen dynamic model to estimate nitrate leaching to groundwater. These estimates were used in developing a groundwater nitrate fate and transport model. The framework considers both point and non-point sources of nitrogen across different land use classes. The methodology was applied for the Sumas–Blaine aquifer of Washington State, US, where heavy dairy industry and berry plantations are concentrated. Simulations were carried out using the developed framework to evaluate the overall impacts of current land use practices and the efficiency of proposed protection alternatives on nitrate pollution in the aquifer

Predicting Streamflows in Snowmelt-Driven Watersheds Using the Flow Duration Curve Method

Predicting streamflows in snow-fed watersheds in the Western United States is important for water allocation. Since many of these watersheds are heavily regulated through canal networks and reservoirs, predicting expected natural flows and therefore water availability under limited data is always a challenge. This study investigates the applicability of the flow duration curve (FDC) method for predicting natural flows in gauged and regulated snow-fed watersheds. Point snow observations, air temperature, precipitation, and snow water equivalent were used to simulate the snowmelt process with the SNOW-17 model, and extended to streamflow simulation using the FDC method with a modified current precipitation index. For regulated watersheds, a parametric regional FDC method was applied to reconstruct natural flow. For comparison, a simplified tank model was used considering both lumped and semi-distributed approaches. The proximity regionalization method was used to simulate streamflows in the regulated watersheds with the tank model. The results showed that the FDC method is capable of producing satisfactory natural flow estimates in gauged watersheds when high correlation exists between current precipitation index and streamflow. For regulated watersheds, the regional FDC method produced acceptable river diversion estimates, but it seemed to have more uncertainty due to less robustness of the FDC method. In spite of its simplicity, the FDC method is a practical approach with less computational burden for studies with minimal data availability

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology