Reassessing water allocation strategies and conjunctive use to reduce water scarcity and scarcity costs for irrigated agriculture in Southern Brazil

The lack of adequate management programs alongside water resources overexploitation have led to undesirable efects such as water shortages and economic losses in several regions. Optimized water allocation strategies using groundwater and surface water resources could reduce water scarcity and scarcity costs by exploring the advantages and peculiarities of each source, thus reducing the efect of variability and uncertainties on water availability. The aim of this study is to assess economic water allocation and the potential of conjunctive use of surface water and groundwater operations using a hydro-economic model to evaluate scarcity and scarcity cost at an irrigated agricultural region in Southern Brazil. Results indicated the possibility to reduce but not entirely eliminate, water scarcity and scarcity cost based solely on the reallocation of water among users and crops, without generating water deficit to users downstream. Results also pointed to the elevated potential of groundwater use as a component to reduce scarcity and its costs, mainly through economic optimized strategies integrated with surface water

Developing a water-energy-GHG emissions modeling framework: Insights from an application to California's water system

[EN] Integrating processes of water and energy interdependence in water systems can improve the understanding of the tradeoffs between water and energy in management and policy. This study presents a development of an integrated water resources management model that includes water-related energy use and GHG emissions. We apply the model to a simplified representation of California's water system. Accounting for water demands from cities, agriculture, environment and the energy sector, and combining a surface water management model with a simple groundwater model, the model optimizes water use across sectors during shortages from an economic perspective, calculating the associated energy use and electricity generation for each water demand. The results of California's water system show that urban end-uses account for most GHG emissions of the entire water cycle, but large water conveyance produces significant peaks over the summer season. Different policy scenarios show the significant tradeoffs between water, energy, and GHG emissions.Escrivà Bou, À.; Lund, J.; Pulido-Velazquez, M.; Hui, R.; Medellín-Azuara, J. (2018). Developing a water-energy-GHG emissions modeling framework: Insights from an application to California's water system. Environmental Modelling & Software. 109:54-65. doi:10.1016/j.envsoft.2018.07.011S546510

A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios

[EN] Ecuador is worldwide considered as one of the main natural flower producers and exporters ¿being roses the most salient ones. Such a fact has naturally led the emergence of small and medium sized companies devoted to the production of quality roses in the Ecuadorian highlands, which intrinsically entails resource usage optimization. One of the first steps towards optimizing the use of resources is to forecast demand, since it enables a fair perspective of the future, in such a manner that the in-advance raw materials supply can be previewed against eventualities, resources usage can be properly planned, as well as the misuse can be avoided. Within this approach, the problem of forecasting the supply of roses was solved into two phases: the first phase consists of the macro-forecast of the total amount to be exported by the Ecuadorian flower sector by the year 2020, using multi-layer neural networks. In the second phase, the monthly demand for the main rose varieties offered by the study company was micro-forecasted by testing seven models. In addition, a Bayesian network model is designed, which takes into consideration macroeconomic aspects, the level of employability in Ecuador and weather-related aspects. This Bayesian network provided satisfactory results without the need for a large amount of historical data and at a low-computational cost.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS ¿Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems¿ (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015. In addition, the authors are greatly grateful by the support given by the SDAS Research Group (www.sdas-group.com)Herrera-Granda, ID.; Lorente-Leyva, LL.; Peluffo-Ordóñez, DH.; Alemany Díaz, MDM. (2021). A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. Lecture Notes in Computer Science. 12566:245-258. https://doi.org/10.1007/978-3-030-64580-9_21S24525812566Asociación de Productores y Exportadores de Flores: Inicio – Expoflores. https://expoflores.com/Palacios, J., Rosero, D.: Análisis de las condiciones climáticas registradas en el Ecuador continental en el año 2013 y su impacto en el sector agrícola. Estud. e Investig. meteorológicas. Ina. Inst. Nac. Meteorol. e Hidrol. Ecuador, 28, p. (2014)Hidalgo-Proaño, M.: Variabilidad climática interanual sobre el Ecuador asociada a ENOS. CienciAmérica 6, 42–47 (2017)Ritchie, J.W., Abawi, G.Y., Dutta, S.C., Harris, T.R., Bange, M.: Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance. Aust. J. Agric. Resour. Econ. 48, 65–93 (2004). https://doi.org/10.1111/j.1467-8489.2004.t01-1-00230.xLetson, D., Podesta, G.P., Messina, C.D., Ferreyra, R.A.: The uncertain value of perfect ENSO phase forecasts: Stochastic agricultural prices and intra-phase climatic variations. Clim. Change 69, 163–196 (2005). https://doi.org/10.1007/s10584-005-1814-9Weber, E.U., Laciana, C., Bert, F., Letson, D.: Agricultural decision making in the argentine Pampas: Modeling the interaction between uncertain and complex environments and heterogeneous and complex decision makers (2008)Loy, J.-P., Pieniadz, A.: Optimal grain marketing revisited a german and polish perspective. Outlook Agric. 38, 47–54 (2009). https://doi.org/10.5367/000000009787762761Wang, Q.J., Robertson, D.E., Haines, C.L.: A Bayesian network approach to knowledge integration and representation of farm irrigation: 1. Model development. WATER Resour. Res. 45 (2009). https://doi.org/10.1029/2006wr005419Keesman, K.J., Doeswijk, T.: uncertainty analysis of weather controlled systems (2010). https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960073961&doi=10.1007%2F978-3-642-03735-1_12&partnerID=40&md5=210525584472097e996a9f124f96fddbSchnepf, R.: U.S. livestock and poultry feed use and availability: background and emerging issues. In: Feed Market Dynamics and U.S. Livestock Implications. pp. 1–36. Nova Science Publishers, Inc., CRS, United States (2012)Medellín-Azuara, J., Howitt, R.E., MacEwan, D.J., Lund, J.R.: Economic impacts of climate-related changes to California agriculture. Clim. Change 109, 387–405 (2011). https://doi.org/10.1007/s10584-011-0314-3McCown, R.L., Carberry, P.S., Dalgliesh, N.P., Foale, M.A., Hochman, Z.: Farmers use intuition to reinvent analytic decision support for managing seasonal climatic variability. Agric. Syst. 106, 33–45 (2012). https://doi.org/10.1016/j.agsy.2011.10.005Scott, S.L., Varian, H.R.: Predicting the present with bayesian structural time series. Available SSRN 2304426 (2013)Prudhomme, C., Shaffrey, L., Woollings, T., Jackson, C., Fowler, H., Anderson, B.: IMPETUS: Improving predictions of drought for user decision-making. International Conference on Drought: Research and Science-Policy Interfacing, 2015. pp. 273–278. CRC Press/Balkema, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom (2015)Wiles, P., Enke, D.: A hybrid neuro-fuzzy model to forecast the Soybean complex. International Annual Conference of the American Society for Engineering Management 2015, ASEM 2015. pp. 1–5. American Society for Engineering Management, Missouri University of Science and Technology, Engineering Management and Systems Engineering Department, United States (2015)Hansen, B.G., Li, Y.: An analysis of past world market prices of feed and milk and predictions for the future. Agribusiness 33, 175–193 (2017). https://doi.org/10.1002/agr.21474Johnson, M.D., Hsieh, W.W., Cannon, A.J., Davidson, A., Bedard, F.: Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods. Agric. For. Meteorol. 218, 74–84 (2016). https://doi.org/10.1016/j.agrformet.2015.11.003Chen, J., Yang, J., Zhao, J., Xu, F., Shen, Z., Zhang, L.: Energy demand forecasting of the greenhouses using nonlinear models based on model optimized prediction method. Neurocomputing 174, 1087–1100 (2016). https://doi.org/10.1016/j.neucom.2015.09.105Fodor, N., et al.: Integrating plant science and crop modeling: assessment of the impact of climate change on soybean and maize production. Plant Cell Physiol. 58, 1833–1847 (2017). https://doi.org/10.1093/pcp/pcx141Chapman, R., et al.: Using Bayesian networks to predict future yield functions with data from commercial oil palm plantations: a proof of concept analysis. Comput. Electron. Agric. 151, 338–348 (2018). https://doi.org/10.1016/j.compag.2018.06.006Lara-Estrada, L., Rasche, L., Sucar, L.E., Schneider, U.A.: Inferring Missing Climate Data for Agricultural Planning Using Bayesian Networks. LAND. 7 (2018). https://doi.org/10.3390/land7010004Abdelaal, H.S.A., Thilmany, D.: Grains production prospects and long run food security in Egypt. Sustain. 11 (2019). https://doi.org/10.3390/su11164457Kusunose, Y., Ma, L., Van Sanford, D.: User responses to imperfect forecasts: findings from an experiment with Kentucky wheat farmers. Weather. Clim. Soc. 11, 791–808 (2019). https://doi.org/10.1175/wcas-d-18-0135.1Kadigi, I.L., et al.: Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: a multivariate empirical (MVE) approach. Agric. Syst. 180 (2020). https://doi.org/10.1016/j.agsy.2019.102693McGrath, G., Rao, P.S.C., Mellander, P.-E., Kennedy, I., Rose, M., van Zwieten, L.: Real-time forecasting of pesticide concentrations in soil. Sci. Total Environ. 663, 709–717 (2019). https://doi.org/10.1016/j.scitotenv.2019.01.401Yang, B., Xie, L.: Bayesian network modelling for “direct farm” mode based agricultural supply chain risk. Ekoloji 28, 2361–2368 (2019)Zaporozhtseva, L.A., Sabetova, T. V, Yu Fedulova, I.: Assessment of the uncertainty factors in computer modelling of an agricultural company operation. International Conference on Information Technologies in Business and Industries, ITBI 2019. Institute of Physics Publishing, Voronezh State Agrarian University, Michurina Str. 30, Voronezh, 394087, Russian Federation (2019)Box, G.E.P., Jenkins, G.M., Reinsel, G.C., Ljung, G.M.: Time series analysis: forecasting and control. Wiley (2015)Hanke, J., Wichern, D.: Business forecast. Pearson Educación (2010)Novagric: Invernaderos para Cultivo de Rosas. https://www.novagric.com/es/invernaderos-rosasWeather Spark: Clima promedio en Quito, Ecuador, durante todo el año - Weather Spark. https://es.weatherspark.com/y/20030/Clima-promedio-en-Quito-Ecuador-durante-todo-el-añoInstituto Nacional de Estadísticas y Censos-INEC: Encuesta Nacional de Empleo, Desempleo y subempleo-ENEMDU. https://www.ecuadorencifras.gob.ec/empleo-diciembre-2019/Central Bank of Ecuador: Central Bank of Ecuador. www.bce.fin.ecHyndman, R., Athnasopoulos, G.: Forecasting: Principles and Practice. OTexts, Australia (2018)Herrera-Granda, I.D., et al.: Artificial neural networks for bottled water demand forecasting: a small business case study. In: Rojas, I., Joya, G.C.A. (eds.) International Work-Conference on Artificial Neural Networks, pp. 362–373. Springer, Canaria (2019

Drought and the Sacramento-San Joaquin Delta, 2012–2016: Environmental Review and Lessons

This paper reviews environmental management and the use of science in the Sacramento–San Joaquin Delta during California’s 2012–2016 drought. The review is based on available reports and data, and guided by discussions with 27 agency staff, stake-holders, and researchers. Key management actions for the drought are discussed relative to four major drought water management priorities stated by water managers: support public health and safety, control saltwater intrusion, preserve cold water in Shasta Reservoir, and maintain minimum protections for endangered species. Despite some success in streamlining communication through interagency task forces, conflicting management mandates sometimes led to confusion about priorities and actions during the drought (i.e., water delivery, the environment, etc.). This report highlights several lessons and offers suggestions to improve management for future droughts. Recommendations include use of pre-drought warnings, timely drought declarations, improved transparency and useful documentation, better scientific preparation, development of a Delta drought management plan (including preparing for salinity barriers), and improved water accounting. Finally, better environmental outcomes occur when resources are applied to improving habitat and bolstering populations of native species during inter-drought periods, well before stressful conditions occur.

Managed Aquifer Recharge as a Tool to Enhance Sustainable Groundwater Management in California

A growing population and an increased demand for water resources have resulted in a global trend of groundwater depletion. Arid and semi-arid climates are particularly susceptible, often relying on groundwater to support large population centers or irrigated agriculture in the absence of sufficient surface water resources. In an effort to increase the security of groundwater resources, managed aquifer recharge (MAR) programs have been developed and implemented globally. MAR is the approach of intentionally harvesting and infiltrating water to recharge depleted aquifer storage. California is a prime example of this growing problem, with three cities that have over a million residents and an agricultural industry that was valued at 47 billion dollars in 2015. The present-day groundwater overdraft of over 100 km3 (since 1962) indicates a clear disparity between surface water supply and water demand within the state. In the face of groundwater overdraft and the anticipated effects of climate change, many new MAR projects are being constructed or investigated throughout California, adding to those that have existed for decades. Some common MAR types utilized in California include injection wells, infiltration basins (also known as spreading basins, percolation basins, or recharge basins), and low-impact development. An emerging MAR type that is actively being investigated is the winter flooding of agricultural fields using existing irrigation infrastructure and excess surface water resources, known as agricultural MAR. California therefore provides an excellent case study to look at the historical use and performance of MAR, ongoing and emerging challenges, novel MAR applications, and the potential for expansion of MAR. Effective MAR projects are an essential tool for increasing groundwater security, both in California and on a global scale. This chapter aims to provide an overview of the most common MAR types and applications within the State of California and neighboring semi-arid regions

Water Banks: What Have We Learnt from the International Experience?

In recent decades, the use of economic instruments has been promoted as a way to improve water demand management, required due to the difficulty of further supply increases. Against this backdrop, this paper analyses the potential of water banks as a type of water market that can provide institutional flexibility in the allocation of water resources among different users. Research has involved an extensive review of the literature, which has allowed us to identify different types of water banks that operate around the world, as well as an analysis of the experiences of water banks implemented to date, in order to assess the performance of this economic instrument in improving water management. This has provided evidence that water banks, if properly implemented, can be a useful tool for improving governance of water resources. Finally, the analysis has enabled us to propose a number of guidelines on how to improve the implementation of water banks in different countries around the worl

Effects of initial aquifer conditions on economic benefits from groundwater conservation

Worldwide, there is growing recognition of the need to reduce agricultural groundwater use in response to rapid rates of aquifer depletion. To date, however, few studies have evaluated how benefits of conservation vary along an aquifer's depletion pathway. To address this question, we develop an integrated modeling framework that couples an agro-economic model of farmers' field-level irrigation decision-making with a borehole-scale groundwater flow model. Unique to this framework is the explicit consideration of the dynamic reductions in well yields that occur as an aquifer is depleted, and how these changes in intraseasonal groundwater supply affect farmers' ability to manage production risks caused by climate variability and, in particular, drought. For an illustrative case study in the High Plains region of the United States, we apply our model to analyze the value of groundwater conservation activities for different initial aquifer conditions. Our results demonstrate that there is a range of initial conditions for which reducing pumping will have long-term economic benefits for farmers by slowing reductions in well yields and prolonging the usable lifetime of an aquifer for high-value irrigated agriculture. In contrast, restrictions on pumping that are applied too early or too late will provide limited welfare benefits. We suggest, therefore, that there are ‘windows of opportunity’ to implement groundwater conservation, which will depend on complex feedbacks between local hydrology, climate, crop growth, and economics

Cost-effectiveness of groundwater conservation measures: A multi-level analysis with policy implications

Groundwater in Spain, as in other arid and semiarid countries worldwide, has been widely used in the expansion of irrigated agriculture. In the Spanish Mancha Occidental aquifer, the excessive, and sometimes illegal, water abstraction for irrigation has promoted outstanding socioeconomic development in the area, but it has also resulted in exploitation of the aquifer and degradation of valuable wetlands. Water policies implemented in the region have not yet managed to restore the aquifer and face strong social opposition. This paper uses a multi-scale modeling approach to explore the environmental and socio-economic impacts of alternative water conservation measures at the farm and basin levels. It also analyzes their comparative cost-effectiveness to help policy makers identify the least costly policy option for achieving the goal of the Mancha Occidental aquifer's sustainability. To conduct this analysis, a Mathematical Programming Model has been developed to simulate: the closing-up and taxed-legalization of unlicensed wells, uniform volumetric and block-rate water prices, water quotas, and water markets. Aggregate results show that net social costs are not substantially different across policy option, so none of the considered policy options will be clearly more cost-effective than the others. However, there are significant differences between private and public costs (at the farm and sub-basin levels), which will be critical for determining the application in practice of these policies. Results show that controlling illegal water mining (through the legalization of unlicensed wells) is necessary, but is not sufficient to recover the aquifer. Rather, effective water management in this area will require the implementation of other water management policies as well. Among them, uniform volumetric and block-rate water pricing policies will entail the lowest net social cost, but will produce important income losses in the smallest and most water-intensive farms, which might put at risk the viability of these farms and the social acceptance of the policies. Further investigations on social costs, policy enforcement capacity and public participation in water management are highly recommende