Econometric Forecasting of Irrigation Water Demand Conserves a Valuable Natural Resource

Natural causes (such as droughts), non-natural causes (such as competing uses), and government policies limit the supply of water for agriculture in general and irrigating crops in particular. Under such reduced water supply scenarios, existing physical models reduce irrigation proportionally among crops in the farmer's portfolio, disregarding temporal changes in economic and/or institutional conditions. Hence, changes in crop mix resulting from expectations about risks and returns are ignored. A method is developed that considers those changes and accounts for economic substitution and expansion effects. Forecasting studies based on this method with surface water in Georgia and Alabama demonstrate the relative strength of econometric modeling vis-à-vis physical methods. Results from a study using this method for ground water in Mississippi verify the robustness of those findings. Results from policy-induced simulation scenarios indicate water savings of 12% to 27% using the innovative method developed. Although better irrigation water demand forecasting in crop production was the key objective of this pilot project, conservation of a valuable natural resource (water) has turned out to be a key consequence.

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Quantifying the Impacts of Compound Extremes on Agriculture and Irrigation Water Demand

10.5194/hess-2020-275 ◽

2020 ◽

Author(s):

Iman Haqiqi ◽

Danielle S. Grogan ◽

Thomas W. Hertel ◽

Wolfram Schlenker

Keyword(s):

Heat Stress ◽

Water Stress ◽

Irrigation Water ◽

Water Demand ◽

Crop Production ◽

Crop Yields ◽

Fold Increase ◽

The United States ◽

Food Prices ◽

Irrigation Water Demand

Abstract. Agricultural production and food prices are affected by hydroclimatic extremes. There has been a large literature measuring the impacts of individual extreme events (heat stress or water stress) on agricultural and human systems. Yet, we lack a comprehensive understanding of the significance and the magnitude of the impacts of compound extremes. Here, we combine a high-resolution weather product with fine-scale outputs of a hydrological model to construct functional indicators of compound hydroclimatic extremes for agriculture. Then, we measure the impacts of individual and compound extremes on crop yields focusing on the United States during the 1981–2015 period. Supported by statistical evidence, we confirm that wet heat is more damaging than dry heat for crops. We show that the average damage from heat stress has been up to four times more severe when combined with water stress; and the value of water experiences a four-fold increase on hot days. In a robust framework with only a few parameters of compound extremes, this paper also improves our understanding of the conditional marginal value (or damage) of water in crop production. This value is critically important for irrigation water demand and farmer decision-making – particularly in the context of supplemental irrigation and sub-surface drainage.

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Potential for sustainable irrigation expansion in a 3 °C warmer climate

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2017796117 ◽

2020 ◽

Vol 117 (47) ◽

pp. 29526-29534

Author(s):

Lorenzo Rosa ◽

Davide Danilo Chiarelli ◽

Matteo Sangiorgio ◽

Areidy Aracely Beltran-Peña ◽

Maria Cristina Rulli ◽

...

Keyword(s):

Climate Change ◽

Irrigation Water ◽

Water Demand ◽

Crop Production ◽

Cropping Systems ◽

Water Storage ◽

Future Research ◽

Irrigation Water Demand ◽

Starting Point ◽

Sustainable Irrigation

Climate change is expected to affect crop production worldwide, particularly in rain-fed agricultural regions. It is still unknown how irrigation water needs will change in a warmer planet and where freshwater will be locally available to expand irrigation without depleting freshwater resources. Here, we identify the rain-fed cropping systems that hold the greatest potential for investment in irrigation expansion because water will likely be available to suffice irrigation water demand. Using projections of renewable water availability and irrigation water demand under warming scenarios, we identify target regions where irrigation expansion may sustain crop production under climate change. Our results also show that global rain-fed croplands hold significant potential for sustainable irrigation expansion and that different irrigation strategies have different irrigation expansion potentials. Under a 3 °C warming, we find that a soft-path irrigation expansion with small monthly water storage and deficit irrigation has the potential to expand irrigated land by 70 million hectares and feed 300 million more people globally. We also find that a hard-path irrigation expansion with large annual water storage can sustainably expand irrigation up to 350 million hectares, while producing food for 1.4 billion more people globally. By identifying where irrigation can be expanded under a warmer climate, this work may serve as a starting point for investigating socioeconomic factors of irrigation expansion and may guide future research and resources toward those agricultural communities and water management institutions that will most need to adapt to climate change.

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Irrigation Water Demand Forecasting Using Wavelet Transforms and Artificial Intelligence

10.13031/2013.38174 ◽

2011 ◽

Author(s):

Jan Franklin Adamowski ◽

Hiu Fung Chan ◽

Inmaculada Pulido-Calvo

Keyword(s):

Artificial Intelligence ◽

Irrigation Water ◽

Water Demand ◽

Wavelet Transforms ◽

Demand Forecasting ◽

Water Demand Forecasting ◽

Irrigation Water Demand

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Agriculture irrigation water demand forecasting based on rough set theory and weighted LS-SVM

2010 Second International Conference on Communication Systems, Networks and Applications ◽

10.1109/iccsna.2010.5588826 ◽

2010 ◽

Cited By ~ 1

Author(s):

Li Xuemei ◽

Ding Lixing ◽

Lv Jinhu

Keyword(s):

Set Theory ◽

Rough Set ◽

Irrigation Water ◽

Water Demand ◽

Rough Set Theory ◽

Demand Forecasting ◽

Water Demand Forecasting ◽

Irrigation Water Demand ◽

Agriculture Irrigation

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Forecast of irrigation water demand considering multiple factors

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-368-331-2015 ◽

2015 ◽

Vol 368 ◽

pp. 331-336

Author(s):

X. Wang ◽

X. Lei ◽

X. Guo ◽

J. You ◽

H. Wang

Keyword(s):

Irrigation Water ◽

Water Demand ◽

Demand Forecasting ◽

Impact Factors ◽

Haihe River Basin ◽

Trend Prediction ◽

Multiple Factors ◽

Irrigation Water Demand ◽

Study Results ◽

Basin Scale

Abstract. Many factors influence irrigation water requirement on the basin scale, which make it difficult to obtain comprehensive data. Despite the advantage of less needing historical data, the prediction precision of traditional trend prediction methods is hard to guarantee. For water scarce basins, the artificial influence on irrigation requirement should be thought of as important impact factors. In this paper, the PCA (principal component analysis) method is used to identify the main influencing factors, such as precipitation, irrigation area, water saving technology and so on. Based on that, an irrigation water demand prediction model considering multiple factors is developed for water shortage regions. The method is applied in the Haihe River basin as an example. The study results show that the irrigation water demand forecasting method considering multiple factors in this paper can achieve higher modelling accuracy, compared with the traditional trend prediction method and the method that does not consider the human influence. In view of the small average relative error, 1.32%, it has good values for application.

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Improved irrigation water demand forecasting using a soft-computing hybrid model

Biosystems Engineering ◽

10.1016/j.biosystemseng.2008.09.032 ◽

2009 ◽

Vol 102 (2) ◽

pp. 202-218 ◽

Cited By ~ 78

Author(s):

Inmaculada Pulido-Calvo ◽

Juan Carlos Gutiérrez-Estrada

Keyword(s):

Soft Computing ◽

Hybrid Model ◽

Irrigation Water ◽

Water Demand ◽

Demand Forecasting ◽

Water Demand Forecasting ◽

Irrigation Water Demand

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An Innovative Fog Catcher System Applied in the Andean Communities of Ecuador

Transactions of the ASABE ◽

10.13031/trans.12368 ◽

2017 ◽

Vol 60 (6) ◽

pp. 1917-1923

Author(s):

David V. Carrera-Villacrés ◽

Iveth Carolina Robalino ◽

Fabian F. Rodríguez ◽

Washington R. Sandoval ◽

Deysi L. Hidalgo ◽

...

Keyword(s):

Sea Level ◽

Water Deficit ◽

Irrigation Water ◽

Water Demand ◽

Agricultural Production ◽

Water Deficits ◽

Irrigation Water Demand ◽

The World ◽

Precipitation Water ◽

Local Water

Abstract. Fog catchers have been successfully applied in several countries around the world. In Ecuador, the Galte communities in the Andean region suffer from water deficits because they are located at an altitude higher than 3500 m above sea level. Rainfall in the area is relatively low, about 600 mm per year, with high evapotranspiration of approximately 615.74 mm per year. This study aimed to install fog catchers in Galte in 2014 and 2015 to help meet the communities’ water needs. The fog catcher system was designed to satisfy the irrigation water demand for local agricultural production, mainly maize, based on estimates using the Blaney-Criddle method. Every day throughout the year, each fog catcher collected 5 to 20 L of water per m2 of catcher area. The results indicate that the fog catcher system can meet about 5% of the local water demand for agricultural production. Keywords: Ecuador, Evaporation, Evapotranspiration, Precipitation, Water deficit.

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