WaterWorks: a decision support tool for irrigation infrastructure decisions at farm level

Increasing water scarcity, climate change and pressure to provide water for environmental flows urge irrigators to be more efficient. In Australia, ongoing water reforms and most recent National Water Security Plan offer incentives to irrigators to adjust their farming practices by adopting water saving irrigation infrastructures to match with soils, crop and climatic conditions. WaterWorks is a decision support tool to facilitate irrigators to make long and short term irrigation infrastructure investment decision at the farm level. It assists irrigators to improve the economic efficiency, water use efficiency and environmental performance of their farm businesses. The WaterWorks has been tested, validated and accepted by the irrigation community and reachers in NSW. The interface of WaterWorks is user-friendly and flexible. The simulation and optimisation module in WaterWorks provides an opportunity to evaluate infrastructure investment decisions to suit their seasonal or long-term water availability. The sensitivity analysis allows substantiating the impact of major variables. Net present value, internal rate of return, benefit cost ratio and payback period are used to analyse the costs and benefits of modern irrigation technology. Application of WaterWorks using a whole farm-level case study indicates its effectiveness in making long term and short term investment decisions. The WaterWorks can be easily integrated into commercial software such as spreadsheets, GIS, real time data acquisition and control systems to further enhance its usability. The WaterWorks can also be used in regional development plannin

Role of aquifer storage and recovery for harmonising irrigation with environment in connected systems

The flows in regulated rivers are strongly dependent on water demand by downstream water users. In irrigated catchments the river flow regimes are alerted to cater for crop demand. The impacts of these altered flows can have significant deleterious ecological impacts. There can be a number of opportunities to manipulate irrigation demand and supply in a way which provide better seasonality of flows and optimise the social, environmental and economic outcomes from water use in a catchment. This paper explores groundwater – surface water substitution as possible way to change water demand patterns. Results of a modelling study show that conjunctive water use through more groundwater extraction or infiltration and extraction is also realistic option capable of replacing over 215GL of peak period surface water use with minimum cost to overall agriculture return. To secure 215GL of water through an aquifer storage and recovery program would cost around $8.96 million

Is hike in inflation responsible for rise in terrorism in Pakistan?

This paper investigates the static and dynamic effect of inflation and economic growth on terrorism using annual frequency i.e. 1971-2010 in case of Pakistan. In doing so, ARDL bounds testing approach to cointegration has been applied while robustness of long run relationship is confirmed by using rolling window approach. The empirical evidence confirms cointegration between inflation, economic growth and terrorism in Pakistan. An increase in inflation raises terrorist attacks. Economic growth is also a major contributor to terrorism. Moreover, bidirectional causality is found between inflation and terrorism as investigated by VECM Granger-causality approach while variance decomposition also supports the findings by VECM analysis.Inflation, Terrorism, Cointegration

Near Optimal Parallel Algorithms for Dynamic DFS in Undirected Graphs

Depth first search (DFS) tree is a fundamental data structure for solving graph problems. The classical algorithm [SiComp74] for building a DFS tree requires $O(m+n)$ time for a given graph $G$ having $n$ vertices and $m$ edges. Recently, Baswana et al. [SODA16] presented a simple algorithm for updating DFS tree of an undirected graph after an edge/vertex update in $\tilde{O}(n)$ time. However, their algorithm is strictly sequential. We present an algorithm achieving similar bounds, that can be adopted easily to the parallel environment. In the parallel model, a DFS tree can be computed from scratch using $m$ processors in expected $\tilde{O}(1)$ time [SiComp90] on an EREW PRAM, whereas the best deterministic algorithm takes $\tilde{O}(\sqrt{n})$ time [SiComp90,JAlg93] on a CRCW PRAM. Our algorithm can be used to develop optimal (upto polylog n factors deterministic algorithms for maintaining fully dynamic DFS and fault tolerant DFS, of an undirected graph. 1- Parallel Fully Dynamic DFS: Given an arbitrary online sequence of vertex/edge updates, we can maintain a DFS tree of an undirected graph in $\tilde{O}(1)$ time per update using $m$ processors on an EREW PRAM. 2- Parallel Fault tolerant DFS: An undirected graph can be preprocessed to build a data structure of size O(m) such that for a set of $k$ updates (where $k$ is constant) in the graph, the updated DFS tree can be computed in $\tilde{O}(1)$ time using $n$ processors on an EREW PRAM. Moreover, our fully dynamic DFS algorithm provides, in a seamless manner, nearly optimal (upto polylog n factors) algorithms for maintaining a DFS tree in semi-streaming model and a restricted distributed model. These are the first parallel, semi-streaming and distributed algorithms for maintaining a DFS tree in the dynamic setting.Comment: Accepted to appear in SPAA'17, 32 Pages, 5 Figure

Renewable and nonrenewable energy consumption, real GDP and CO2 emissions nexus: a structural VAR approach in Pakistan

Any rise in real GDP crafts higher energy demand in Pakistan. This short-term rising energy requirement is fulfilled with the help of nonrenewable and renewable energy consumption, but nonrenewable energy consumption adds more in it. The rise in nonrenewable energy consumption lifts real GDP up in short-run. Forecast error variance decomposition illustrates nonrenewable energy consumption alone passes 87% variation in the CO2 emissions. This verifies fossil fuels are accountable for environmental degradation in Pakistan. The CO2 emissions worsen economic activity, real GDP falls but renewable energy consumption augments. This elevation in renewable energy consumption is the proof of stabilization efforts that are being initiated by official authorities as CO2 emissions reach to alarming level. The rise in renewable energy consumption boosts economic activity, and real GDP breeds. Most of times, an increase in renewable energy consumption is an effort to substitute it with nonrenewable energy consumption, resulting in lower level of CO2 emissions.Energy Consumption, Real GDP, CO2 Emissions

Does defence spending impede economic growth? cointegration and causality analysis for Pakistan

This study revisits the relationship between defence spending and economic growth using Keynesian model in Pakistan by applying ARDL bounds testing approach to cointegration for long run and error correction method for short span of time. Empirical evidence suggests a stable cointegration relationship between defence spending and economic growth. An increase in defence spending retards the pace of economic growth confirming the validation of Keynesian hypothesis in the country. Current economic growth is positively linked with economic growth in previous period while rise in nonmilitary expenditures boosts economic growth. Interest rate is inversely associated with economic growth. Finally, unidirectional causality running from military spending to economic growth is found.Defence Spending, Economic Growth, Cointegration, Causality, Pakistan

Does economic growth cause terrorism in Pakistan?

This paper analyzes the relationship between terrorism and economic growth for Pakistan by incorporating capital and trade openness. We used the data from 1971-2010 and have applied ARDL bounds testing approach to cointegration to examine the long run relationship between the variables. The VECM Granger causality approach is used to detect the direction of causality between terrorism and economic growth. Our empirical results confirm the existence of long run relationship between economic growth and terrorism. The Granger causality analysis indicates bidirectional causality between terrorism and capital, trade openness and capital, and terrorism and trade openness. However, unidirectional causality is found running from economic growth to terrorism.Terrorism, Economic Growth, Cointegration and Causality

Does Military Spending Explode External Debt in Pakistan?

This paper explores the effect of military expenditures on external debt in case of Pakistan over the period of 1973-2009. For this purpose, ARDL bounds testing approach is used to examine cointegration between the variables. ADF, P-P and ADF-GLS, Clemente et al. (1998) unit root tests are applied to check the order of integration of variables. OLS and ECM regressions approaches are employed to investigate marginal impact of military spending on external debt in long and short run. Our findings indicate cointegration which confirms long run relationship between military expenditures, external debt, economic growth and investment. The results reveal that a rise in military expenditures increases the stock of external debt. The inverse effect of economic growth on external debt is found and an increase in investment is also increasing external debt in the country. This study invites policy makers to approach the problem of curtailing external debt in innovative ways in case of Pakistan.Military Spending, External Debt, Cointegration

Environmental Kuznets Curve and the role of energy consumption in Pakistan

The paper is an effort to fill the gap in the energy literature with a comprehensive country study for Pakistan. We investigate the relationship between CO2 emissions, energy consumption, economic growth and trade openness for Pakistan over the period of 1971-2009. Bounds test for cointegration and Granger causality test are employed for the empirical analysis. The result suggests that there exists long-run relationship among the variables and the Environmental Kuznets Curve (EKC) hypothesis is supported. The significant existence of EKC shows the country's effort to condense CO2 emissions and indicates a reasonable achievement of controlling environmental degradation in Pakistan. Furthermore, we find one-way causal relationship running from income to CO2 emissions. Energy consumption increases CO2 emissions both in the short and long runs. Trade openness reduces CO2 emissions in the long run but it is insignificant in the short run. In addition, the change in CO2 emissions from short run to the long span of time is corrected by about 10 percent each year.CO2 emissions, energy consumption, trade openness

Does financial instability increase environmental pollution in Pakistan?

The present aims to explore the relationship between financial instability and environmental degradation within multivariate framework using time series data for the period1972-2009 in case of Pakistan. The long run relationship is investigated by ARDL bounds testing approach to cointegration, and error correction method is applied to examine short sun dynamics. The stationarity properties of the variables are tested by applying Saikkonen and Lütkepohl (2002) structural break unit root test. Empirical evidence confirms the existence of long run relationship while financial instability increases environmental pollution in the country.Financial Instability, Environment, Cointegration