Understanding Human Adaptation to Drought: Agent-Based Agricultural Water Demand Modeling in the Bow River Basin, Canada

2021 ◽  
Author(s):  
Mohammad Ghoreishi ◽  
Saman Razavi ◽  
Amin Elshorbagy
Keyword(s):  
River Basin ◽  
Water Demand ◽  
Human Adaptation ◽  
Agricultural Water ◽  
Agent Based ◽  
Demand Modeling ◽  
Adaptation To Drought

Variation in agricultural water demand and its attributions in the arid Tarim River Basin

2018 ◽  
Vol 156 (3) ◽  
pp. 301-311 ◽  
Author(s):  
G. Fang ◽  
Y. Chen ◽  
Z. Li
Keyword(s):  
River Basin ◽  
Water Demand ◽  
Sunshine Duration ◽  
Irrigation Management ◽  
High Rate ◽  
Tarim River ◽  
Tarim River Basin ◽  
Agricultural Water ◽  
Natural Ecosystems ◽  
Increase Rate

AbstractAgricultural water use accounts for more than 95% of the total water consumption in the extreme arid region of the Tarim River Basin. Understanding the variation of agricultural water demand (AWD) and its attributions is therefore vital for irrigation management and water resource allocation affecting the economy and natural ecosystems in this high water-deficit region. Here spatial–temporal variations of AWD based on weighted crop water requirement (ETc) were estimated using the Penman–Monteith equation and the crop coefficient approach. Then the contributions of meteorological factors and planting structure (i.e. proportions of crop acreages) to AWD variations were quantified based on traditional methods and numerical experiment (i.e. a series calculation of AWD based on different input data). Results indicated that AWD decreased during 1960–1988 at a rate of 2.76 mm/year and then started to increase at a high rate of 9.47 mm/year during 1989–2015. For the first period (1960–1988), wind speed (uz), maximum humidity (RHmax) and sunshine duration (n) were the most important factors leading to decreased AWD, while for the second period the evolution of planting structure was the most significant factor resulting in the rapid increase of AWD, followed by the minimum temperature (Tmin), uz and RHmax. The evolution of planting structure alone would lead to an increase rate for AWD of 7.1 mm/year while the climatic factor would result in an increase rate of 1.9 mm/year during 1989–2015.

Exploring Northwest China's agricultural water-saving strategy: analysis of water use efficiency based on an SE-DEA model conducted in Xi'an, Shaanxi Province

2016 ◽  
Vol 74 (5) ◽  
pp. 1106-1115 ◽  
Author(s):  
L. Mu ◽  
L. Fang ◽  
H. Wang ◽  
L. Chen ◽  
Y. Yang ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Use Efficiency ◽  
Water Use ◽  
Water Demand ◽  
Water Governance ◽  
Northwest China ◽  
Water Saving ◽  
Shaanxi Province ◽  
Agricultural Water ◽  
Use Efficiency

Worldwide, water scarcity threatens delivery of water to urban centers. Increasing water use efficiency (WUE) is often recommended to reduce water demand, especially in water-scarce areas. In this paper, agricultural water use efficiency (AWUE) is examined using the super-efficient data envelopment analysis (DEA) approach in Xi'an in Northwest China at a temporal and spatial level. The grey systems analysis technique was then adopted to identify the factors that influenced the efficiency differentials under the shortage of water resources. From the perspective of temporal scales, the AWUE increased year by year during 2004–2012, and the highest (2.05) was obtained in 2009. Additionally, the AWUE was the best in the urban area at the spatial scale. Moreover, the key influencing factors of the AWUE are the financial situations and agricultural water-saving technology. Finally, we identified several knowledge gaps and proposed water-saving strategies for increasing AWUE and reducing its water demand by: (1) improving irrigation practices (timing and amounts) based on compatible water-saving techniques; (2) maximizing regional WUE by managing water resources and allocation at regional scales as well as enhancing coordination among Chinese water governance institutes.

Remote sensing of agricultural water demand information: A California study

1978 ◽  
Vol 14 (2) ◽  
pp. 170-176 ◽  
Author(s):  
John E. Estes ◽  
John R. Jensen ◽  
Larry R. Tinney
Keyword(s):  
Remote Sensing ◽  
Water Demand ◽  
Agricultural Water ◽  
Demand Information

scholarly journals Multivariate Statistical Analysis for Water Demand Modeling

2014 ◽  
Vol 89 ◽  
pp. 901-908 ◽  
Author(s):  
C.M. Fontanazza ◽  
V. Notaro ◽  
V. Puleo ◽  
G. Freni
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Water Demand ◽  
Multivariate Statistical ◽  
Demand Modeling

scholarly journals How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

2020 ◽  
Vol 12 (7) ◽  
pp. 2869
Author(s):  
Xiling Zhang ◽  
Yusheng Kong ◽  
Xuhui Ding
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Utilization Efficiency ◽  
The Yellow River ◽  
Agricultural Water ◽  
High Quality ◽  
Water Utilization ◽  
Urban Rural ◽  
The Yellow River Basin

To promote the high-quality development of the Yellow River Basin, the total amount and intensity of agricultural water must be controlled. Further speaking, an urbanization development system should be established that is compatible with water resources and the water environment. We adopted the stochastic frontier analysis model to measure the agricultural water utilization efficiency of the Yellow River Basin from 2007 to 2017. We also adopted the dynamic panel difference generalized method of moments (GMM) and system GMM models to verify the driving factors, in which population urbanization, economic urbanization, and equilibrium urbanization levels were selected as the key variables. The results show that the overall efficiency of agricultural water utilization maintained a steady upward trend during the research period. The spatial differentiation was generally characterized by higher efficiency levels in the eastern region and lower levels in the western region. The variation coefficient of water utilization efficiency showed a downward trend in general, which indicates a space spillover effect. Agricultural water utilization efficiency continued to converge from 2007 to 2017, and the upper reaches area converged relatively more quickly. Regarding the influencing factors, the population urbanization, economic urbanization, balanced urbanization, crop planting ratio, and rice planting ratio had negative effects on agricultural water utilization efficiency. Urbanization did not positively affect agricultural water use efficiency as the related theories, so urbanization quality and urban–rural integration should be paid more attention. However, technology innovation was significantly positive in agricultural water utilization efficiency. The influencing factors of per capita water availability and annual precipitation did not pass the significance test. Therefore, the government should vigorously promote the development of high-quality new-type urbanization, scientifically formulate the scale and speed of urbanization, strengthen the urban, rural, and industrial integration, and promote the adjustment of planting structures and agricultural deep processing.

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