Hector Malano

Penman-Monteith, FAO-24 reference crop evapotranspiration and class-A pan data in Australia

Abstract The Food and Agriculture Organisation (FAO) methods are recognised as the international standard for estimating reference crop evapotranspiration (ETo). The Penman-Monteith method is currently favoured by the FAO over the FAO-24 methods. The FAO also recommends alternative methods which may be used where there are limited data. In this paper, ETo, estimated using the Penman-Monteith and FAO-24 methods and class-A pan data for 16 Australian locations with a wide range of climate conditions are compared. The analyses indicate that the FAO-24 Penman ETo, estimates are generally 20 to 40% higher than the Penman-Monteith estimates. However, the FAO-24 Radiation and Penman-Monteith methods give similar daily ETo, estimates. Unlike Penman-Monteith, which also requires windspeed data, the FAO-24 Radiation method estimates ETo. from temperature and sunshine hours, climate variables which are relatively conservative in space. The FAO-24 Radiation method can thus be used as a surrogate for Penman-Monteith to estimate daily ETo, for areas where windspeed data are not available. The FAO-24 Blaney-Criddle method, which uses only temperature data, gives similar monthly ETo, estimates as Penman-Monteith, and is therefore adequate for applications where only long-term ETo, estimates are required. The comparisons also show that there is a satisfactory correlation between class-A pan data and Penman-Monteith ETo, for evaporation totals over 3 or more days. However, the pan coefficient is very dependent on local climate and physical conditions, and it should be determined by comparing the pan data with either the Penman-Monteith or FAO-24 Radiation (ETo). estimates.

Management of Water Resources

Recent reforms in water resources management in the Murray-Darling Basin are discussed from the perspective of water allocation, water rights, irrigation, and the environment, with particular reference to differences between details in the states of Victoria and New South Wales. A similar review of water resources management is made for Vietnam with some further discussion of the new water law of 1998. Contextual differences are discussed and the opportunities for Vietnam to make use of Australian experience are briefly analysed.

Integrated River Basin Management in the Multi-jurisdictional River Basins: The Case of the Mekong River Basin

Achieving integrated river basin management in large multi-jurisdictional river basins is a difficult task. In the Mekong River basin some of the countries have begun to implement a cooperative framework, which indicates a desire to achieve a form of integrated management. Significant progress has been made but results still fall short of the ideal. The primary reasons for this includes the lack of institutional capacity of the multi-jurisdictional cooperative authority and its counterpart organizations in each of the participating countries, together with a lack of political drive to develop integrated management as a priority.

Multiple Model Predictive Flood Control in Regulated River Systems with Uncertain Inflows

This paper presents a novel approach to real time automatic flood control in a managed river network that is subject to uncertain inflows. The proposed approach uses multiple models to represent inflows ranging from low to high flow. Optimal model selection is achieved in a minimum mean square error sense using a bank of Kalman filters to identify the most likely inflow characteristic. There are no a-priori probabilities assigned to the individual models. Model Predictive Control is used for water level controller design. Our Adaptive Multi Model Predictive Control (AMMPC) method is proposed as an alternative to existing techniques that also use multiple inflow models but with a-priori inflow model probabilities, either weighted or equally likely. The performance of the approach is demonstrated using a simulated river-reservoir model as well as using data collected at the Wivenhoe Dam during the 2011 floods in Queensland, Australia.

Asset Management for Irrigation and Drainage Infrastructure – Principles and Case Study

This paper presents the general principles and functions of asset management for irrigation and drainage infrastructure: Asset planning and creation strategies, operation and maintenance, performance monitoring, accounting and economics and audit and renewal analysis. The various elements of the program are conceptually defined and their application is illustrated with the asset management program (AMP) formulated for the La Khe Irrigation System in Vietnam. It also identifies the role of the AMP within the framework of service oriented management of irrigation and drainage services. An infrastructure and investment profile developed from the asset survey identified the investment requirement over the next 40 years. The analysis of cost of service and revenues shows a shortfall of US£17.00/ha/annum to meet the investment requirement over this period. The asset audit and renewal analysis shows the upgrades of the main system needed to improve the current level of service.

Irrigation control based on model predictive control (MPC)

This research proposes A THEORETICAL FRAMEWORK based on model predictive control (MPC) for irrigation control to minimize both root zone soil moisture deficit (RZSMD) and irrigation amount under a limited water supply. We (i) investigate means to incorporate direct measurements to MPC (ii) introduce two Robust MPC techniques - Certainty Equivalence control (CE) and Disturbance Affine Feedback Control (DA) - to mitigate the uncertainty of weather forecasts, and (iii) provide conditions to obtain two important theoretical aspects of MPC - feasibility and stability - in the context of irrigation control. Our results show that system identification enables automation while incorporating direct measurements. Both DA and CE minimize RZSMD and irrigation amount under uncertain weather forecasts and always maintain soil moisture above wilting point subject to water availability. The theoretical results are compared against the model AQUACROP, weather data and forecasts from Shepparton, Australia. We also discuss the performance of Robust MPC under different water availability, soil, crop conditions. In general, MPC shows to be a promising tool for irrigation control. MPC is used to minimize both root zone soil moisture deficit and irrigation amount.System identification incorporates direct measurements to MPC enabling automation.Uncertainty in weather forecasts is mitigated using two modified Robust MPC approaches.Optimal operation can be guaranteed through the proposed method.Guaranteed operation above wilting point at all times subject to water availability.

Application of the analytic hierarchy process to prioritise irrigation asset renewals: the case of the La Khe irrigation scheme, Vietnam

In recent years, many organisations responsible for economic infrastructure have developed asset management systems to improve the financial and service performance of their facilities. Asset management is an integrated approach to improving the ability of an irrigation system to deliver water at a defined level of service in the most cost‐effective manner. This paper describes how the analytic hierarchy process (AHP) is applied to identify priorities for asset renewals in the La Khe irrigation scheme in North Vietnam. The AHP methodology was coupled with the expected maximum utility (EMU) to evaluate renewal priorities of assets grouped by types and by location within the hydraulic system.

Model Predictive Control for Real-Time Irrigation Scheduling

Abstract Irrigation underpins agricultural productivity. The purpose of irrigation is to match water supply to crop water demand. The effectiveness of irrigation depends on the quality of the timing and duration of watering events, also called irrigation scheduling. Most farmers use heuristic rules to determine irrigation events. This often leads to over-watering which results in lower crop yields and wasted water. By acquiring good estimates of a plants water demand and local weather, it is possible to use optimization theory to compute an irrigation schedule that matches supply and demand thereby improving crop yields. Previous work has focused on scheduling irrigation over long time frames such as seasonal water allocations. Real-time irrigation scheduling, e.g. hourly or daily, has received little attention. Farmers rely on heuristic approaches implemented using simple spreadsheet tools to help them in this task. This approach cannot deal effectively with operational constraints and thereby results in poor performance. In this paper we develop a Model Predictive Control framework for real-time irrigation scheduling. The proposed formulation can take into account common operational constraints, including limitations on water availability as well as practical limits on the maximum or minimum amount of water that should be applied. We use measured climate data coupled with a simulation model to evaluate the proposed algorithm.

Ranking and classification of irrigation system performance using fuzzy set theory: case studies in Australia and China

A methodology for ranking and classifying performance of irrigation systems through multidimensional performance indicators is developed using fuzzy set theory. The procedure uses the concepts of fuzzy resemblance and fuzzy dominance. Preference levels reflecting management priorities are incorporated into the analysis using appropriate weighting factors. The application of the procedure is demonstrated through two case studies: the Shi-Jin irrigation district in Hebei Province, China and the Goulburn irrigation region in Victoria, Australia. The classification of performance periods for the Australian system shows three clusters indicating the predominant effect of the increase in waterlogged area when higher priority is given to this indicator. No clear trend appeared when equal weight was assigned to all indicators. The effect of economic reforms implemented in 1977–78 in China is clearly reflected in the resulting ranking and clustering of the performance periods in the Shi-Jin irrigation district. Performance levels following reforms are shown to be consistently higher.

Mapping Flooded Rice Paddies Using Time Series of MODIS Imagery in the Krishna River Basin, India

Abstract: Rice is one of the major crops cultivated predominantly in flooded paddies, thus a large amount of water is consumed during its growing season. Accurate paddy rice maps are therefore important inputs for improved estimates of actual evapotranspiration in the agricultural landscape. The main objective of this study was to obtain flooded paddy rice maps using multi-temporal images of Moderate Resolution Imaging Spectroradiometer (MODIS) in the Krishna River Basin, India. First, ground-based spectral samples collected by a field spectroradiometer, CROPSCAN, were used to demonstrate unique contrasts between the Normalized Difference Vegetation Index (NDVI) and the Land Surface Water Index (LSWI) observed during the transplanting season of rice. The contrast between Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) from MODIS time series data was then used to generate classification decision rules to map flooded rice paddies, for the transplanting seasons of Kharif