Reallocating regional water apparent productivity in the long term: methodological contributions and application for Spain

Cazcarro, Ignacio; Martín-Retortillo, Miguel; Serrano, Ana

doi:10.1007/s10113-019-01485-9

Cited by 8 publications

(10 citation statements)

References 57 publications

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“…It mainly decomposes the total increment from different layers and quantifies the contribution of structural changes from different levels to the total increment, in which it has achieved remarkable results. In addition, the method has been successfully applied in the studies of water resources (Cazcarro et al, 2019;Llop, 2019). LMDI can completely decompose the multiple related factors at the same time.…”

Section: Introductionmentioning

confidence: 99%

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau, China

Dai

Chen

2020

J. Arid Land

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Soil erosion in the Three-River Headwaters Region (TRHR) of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment. Vegetation and precipitation are considered to be the main factors for the variation in soil erosion. However, it is a big challenge to analyze the impacts of precipitation and vegetation respectively as well as their combined effects on soil erosion from the pixel scale. To assess the influences of vegetation and precipitation on the variation of soil erosion from 2005 to 2015, we employed the Revised Universal Soil Loss Equation (RUSLE) model to evaluate soil erosion in the TRHR, and then developed a method using the Logarithmic Mean Divisia Index model (LMDI) which can exponentially decompose the influencing factors, to calculate the contribution values of the vegetation cover factor (C factor) and the rainfall erosivity factor (R factor) to the variation of soil erosion from the pixel scale. In general, soil erosion in the TRHR was alleviated from 2005 to 2015, of which about 54.95% of the area where soil erosion decreased was caused by the combined effects of the C factor and the R factor, and 41.31% was caused by the change in the R factor. There were relatively few areas with increased soil erosion modulus, of which 64.10% of the area where soil erosion increased was caused by the change in the C factor, and 23.88% was caused by the combined effects of the C factor and the R factor. Therefore, the combined effects of the C factor and the R factor were regarded as the main driving force for the decrease of soil erosion, while the C factor was the dominant factor for the increase of soil erosion. The area with decreased soil erosion caused by the C factor (12.10×10 3 km 2 ) was larger than the area with increased soil erosion caused by the C factor (8.30×10 3 km 2 ), which indicated that vegetation had a positive effect on soil erosion. This study generally put forward a new method for quantitative assessment of the impacts of the influencing factors on soil erosion, and also provided a scientific basis for the regional control of soil erosion.

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Section: Introductionmentioning

confidence: 99%

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau, China

Dai

Chen

2020

J. Arid Land

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“…For the most part, economists' contributions to the virtual water (VW) and WF literature have not been as comprehensive as it should either. These contributions have focused on: a) computing VW and WF through economic tools such as multiregional input-output tables and models (Duarte and Yang, 2011;Tian et al, 2018); b) criticize or highlight limitations on the concept of VW based on the theory of comparative advantage (Wichelns, 2011;Gawel, 2014;Mateo-Sagasta et al, 2015;Wichelns, 2015); c) defend it or further explain factors completing the picture (Gawel, 2014;Afkhami et al, 2018;Zhao et al, 2019); and d) relate WF with scarcity and profitability, to obtain a visible 'water productivity' (Garrido et al, 2010;Cazcarro et al, 2019).…”

Section: Some Ideas On How To Improve Relevance In Practical Water Mamentioning

confidence: 99%

“…Typically, less precision in the agri-food WFs, and short temporal spans. (Garrido et al, 2010;Cazcarro et al, 2019) WF, scarcity, and water apparent productivity Highlight the role of dryland/ irrigated land, and the relation of WF to scarcity and water apparent productivities.…”

Section: Lack Of Sensitivity Analyses On Key Assumptionsmentioning

confidence: 99%

Blind Spots in Water Management, and How Natural Sciences Could Be Much More Relevant

Cazcarro

Bielsa

2020

Front. Plant Sci.

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“…Almost all of this growth took place between 1995 and 2015. An additional advantage of this case study is that in recent years abundant literature has been produced analysing the water footprint of Spanish agriculture from a long-term perspective, similar to our case [33][34][35][36][37][38][39][40]. This profuse literature can be explained by the important role that irrigation has played in the increase in Spain's agricultural production since the mid twentieth century [41] and the intense conflicts that have arisen with respect to its distribution across territories and economic agents [33,42,43].…”

Section: Introductionmentioning

confidence: 99%

“…These analyses conclude that 80% of water use in Spain corresponds to agriculture [46]. The estimates of the blue water footprint of Spanish agricultural crop production oscillate between 11.9 km 3 [47] and 15.6 km 3 for the year 2001 [48] or 15.8 km 3 for 2010 [35]. From a long-term perspective, the increase has been enormous.…”

Section: Introductionmentioning

confidence: 99%

The Blue Water Footprint of the Spanish Wine Industry: 1935–2015

Ayuda

Esteban

Martín-Retortillo

et al. 2020

Water

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The impact of economic growth on natural resources and the environment constitutes a fundamental topic in current research. In particular, water, a fundamental resource for human beings, has been subject to intense pressure in recent decades. Within this context, this article examines the growth of the blue water footprint of the Spanish wine industry and its environmental impact. In order to do this, we will first calculate the blue water footprint of wine, using a bottom-up methodology. Our methodology introduces certain advances with respect to those usually used. Our results show a very fast increase of the blue water footprint from 1995, which has multiplied six-fold in twenty years with an extreme concentration in the region of Castilla-La Mancha, which accounts for 70% of this increase. The expansion of irrigated vine growing in this region has played a relevant role in the serious problems suffered by its aquifers.

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Reallocating regional water apparent productivity in the long term: methodological contributions and application for Spain

Cited by 8 publications

References 57 publications

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau, China

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau, China

Blind Spots in Water Management, and How Natural Sciences Could Be Much More Relevant

The Blue Water Footprint of the Spanish Wine Industry: 1935–2015

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