. State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Beijing 100083, China . National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733000, China . Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
Amid the escalating frequency of climate extremes, it is crucial to determine their impact on agricultural water scarcity to preserve agricultural development. Current research does not often examine how different spatial scales and compound climate extremes influence agricultural water scarcity. Using an agricultural water scarcity index (AWSI), this study examined the effects of precipitation and temperature extremes on AWSI across secondary and tertiary river basins in China from 1971 to 2010. The results indicated a marked increase in AWSI during dry years and elevated temperatures. The analysis underscores that precipitation had a greater impact on AWSI than temperature variation. In secondary basins, AWSI was about 26% higher than the long-term average during dry years, increasing to nearly 49% in exceptionally dry conditions. By comparison, in tertiary basins, the increases were 28% and 55%, respectively. In hot years, AWSI rose by about 6.8% (7.3% for tertiary basins) above the average, surging to about 19.1% (15.5% for tertiary basins) during extremely hot periods. These results show that AWSI assessment at the tertiary basin level better captured the influence of climate extremes on AWSI than assessments at the secondary basin level, which highlights the critical importance of a finer spatial scale for a more precise assessment and forecast of water scarcity within basin scales. Also, this study has highlighted the paramount urgency of implementing strategies to tackle water scarcity issues under compound extreme dry and hot conditions. Overall, this study offers an in-depth evaluation of the influence of both precipitation and temperature variation, and research scale on water scarcity, which will help formulate better water resource management strategies.
Online First Date: 20 September 2024Issue Date: 12 November 2024
Cite this article:
Jiongjiong LIU,Yilin ZHAO,Wenfeng LIU. Impact of climate extremes on agricultural water scarcity and the spatial scale effect[J]. Front. Agr. Sci. Eng. ,
2024, 11(4): 515-526.
Fig.1 Distribution of annual average precipitation and temperature for secondary (a, c) and tertiary (b, d) river basins (审图号: GS 京（2024）1698号).
Fig.2 Average agricultural water scarcity index (AWSI) in China from 1971 to 2010 aggregated to secondary (a) and tertiary (b) river basin levels (审图号: GS 京（2024）1698号).
Fig.3 Relative changes in agricultural water scarcity index (AWSI) resulting from precipitation and temperature anomalies across secondary (a) and tertiary (b) river basins. The datasets comprise 2320 and 8480 basin-year samples for secondary and tertiary river basins, respectively.
Fig.4 Variations in the agricultural water scarcity index (AWSI) in response to precipitation and temperature anomalies. Each subplot illustrates the overall relative change (%) in AWSI, adjusted for basin areas, using data from basin-year samples. Error bars in the graphs represent a 95% confidence intervals, calculated from 1000 bootstrap estimates. Years with precipitation anomalies lower than ?1.0 standard deviation (σ) are classified as dry years whereas those with anomalies higher than 1.0σ are considered wet years for secondary (a) and tertiary (b) river basins. Similarly, temperature anomalies below ?1.0σ categorize years as cold and those above 1.0σ as hot for secondary (c) and tertiary (d) river basins.
Fig.5 Basin-year sample ratios (%) with different precipitation and temperature anomalies for secondary (a, c) and tertiary (b, d) river basins.
Fig.6 Relative changes (RC) in agricultural water scarcity index (AWSI) from multiyear averages under dry and hot conditions for secondary and tertiary basins (审图号: GS 京（2024）1698号). Dry conditions for secondary (a) and tertiary (b) basins, and hot conditions for secondary (c) and tertiary (d) basins.
Fig.7 Relative changes (RC) in agricultural water scarcity index (AWSI) from multiyear averages under compound dry and hot conditions for secondary (a) and tertiary (b) river basins (审图号: GS 京（2024）1698号). White color indicates no compound dry and hot conditions.
W, Liu X, Liu H, Yang P, Ciais Y Wada . Global water scarcity assessment incorporating green water in crop production. Water Resources Research, 2022, 58(1): e2020WR028570
3
M Falkenmark . Growing water scarcity in agriculture: future challenge to global water security. Philosophical Transactions of the Royal Society A: Mathematical Physical and Engineering Sciences, 2013, 371(2002): 20120410
Y, Qin N D, Mueller S, Siebert R B, Jackson A, AghaKouchak J B, Zimmerman D, Tong C P, Hong S J Davis . Flexibility and intensity of global water use. Nature Sustainability, 2019, 2(6): 515–523 https://doi.org/10.1038/s41893-019-0294-2
6
J, Schewe J, Heinke D, Gerten I, Haddeland N W, Arnell D B, Clark R, Dankers S, Eisner B M, Fekete F J, Colón-González S N, Gosling H, Kim X C, Liu Y, Masaki F T, Portmann Y, Satoh T, Stacke Q H, Tang Y, Wada D, Wisser T, Albrecht K, Frieler F, Piontek L, Warszawski P Kabat . Multimodel assessment of water scarcity under climate change. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(9): 3245–3250 https://doi.org/10.1073/pnas.1222460110
7
J, Liu Z, Fu W Liu . Impacts of precipitation variations on agricultural water scarcity under historical and future climate change. Journal of Hydrology, 2023, 617(Part B): 128999
8
X, Liu W, Liu Q, Tang B, Liu Y, Wada H Yang . Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change. Earth’s Future, 2022, 10(4): e2021EF002567
9
J, Liu H, Yang S N, Gosling M, Kummu M, Flörke S, Pfister N, Hanasaki Y, Wada X, Zhang C, Zheng J, Alcamo T Oki . Water scarcity assessments in the past, present, and future. Earth’s Future, 2017, 5(6): 545–559 https://doi.org/10.1002/2016EF000518
10
X, Cao M, Wu X, Guo Y, Zheng Y, Gong N, Wu W Wang . Assessing water scarcity in agricultural production system based on the generalized water resources and water footprint framework. Science of the Total Environment, 2017, 609: 587–597 https://doi.org/10.1016/j.scitotenv.2017.07.191
11
X, Gao C A, Schlosser C, Fant K Strzepek . The impact of climate change policy on the risk of water stress in southern and eastern Asia. Environmental Research Letters, 2018, 13(6): 064039 https://doi.org/10.1088/1748-9326/aaca9e
12
P, Greve T, Kahil J, Mochizuki T, Schinko Y, Satoh P, Burek G, Fischer S, Tramberend R, Burtscher S, Langan Y Wada . Global assessment of water challenges under uncertainty in water scarcity projections. Nature Sustainability, 2018, 1(9): 486–494 https://doi.org/10.1038/s41893-018-0134-9
13
X, Zhao J, Liu Q, Liu M R, Tillotson D, Guan K Hubacek . Physical and virtual water transfers for regional water stress alleviation in China. Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(4): 1031–1035 https://doi.org/10.1073/pnas.1404130112
14
C J, Vörösmarty E M, Douglas P A, Green C Revenga . Geospatial indicators of emerging water stress: an application to Africa. Ambio, 2005, 34(3): 230–236 https://doi.org/10.1579/0044-7447-34.3.230
15
L, Zhuo B, Feng P Wu . Water footprint study review for understanding and resolving water issues in China. Water, 2020, 12(11): 2988 https://doi.org/10.3390/w12112988
16
S, Kang X, Hao T, Du L, Tong X, Su H, Lu X, Li Z, Huo S, Li R Ding . Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agricultural Water Management, 2017, 179: 5–17 https://doi.org/10.1016/j.agwat.2016.05.007
17
W, Zhu S, Jia N, Devineni A, Lv U Lall . Evaluating China’s water security for food production: the role of rainfall and irrigation. Geophysical Research Letters, 2019, 46(20): 11155–11166 https://doi.org/10.1029/2019GL083226
18
H, Cheng Y, Hu J Zhao . Meeting China’s water shortage crisis: current practices and challenges. Environmental Science & Technology, 2009, 43(2): 240–244 https://doi.org/10.1021/es801934a
19
S N, Gosling N W Arnell . A global assessment of the impact of climate change on water scarcity. Climatic Change, 2016, 134(3): 371–385 https://doi.org/10.1007/s10584-013-0853-x
20
N, Hanasaki S, Fujimori T, Yamamoto S, Yoshikawa Y, Masaki Y, Hijioka M, Kainuma Y, Kanamori T, Masui K, Takahashi S Kanae . A global water scarcity assessment under Shared Socio-economic Pathways—Part 1: water use. Hydrology and Earth System Sciences, 2013, 17(7): 2375–2391 https://doi.org/10.5194/hess-17-2375-2013
21
N, Hanasaki S, Fujimori T, Yamamoto S, Yoshikawa Y, Masaki Y, Hijioka M, Kainuma Y, Kanamori T, Masui K, Takahashi S Kanae . A global water scarcity assessment under Shared Socio-economic Pathways—Part 2: water availability and scarcity. Hydrology and Earth System Sciences, 2013, 17(7): 2393–2413 https://doi.org/10.5194/hess-17-2393-2013
22
X, Liu Q, Tang W, Liu T I E, Veldkamp J, Boulange J, Liu Y, Wada Z, Huang H Yang . A spatially explicit assessment of growing water stress in China from the past to the future. Earth’s Future, 2019, 7(9): 1027–1043 https://doi.org/10.1029/2019EF001181
23
M, Falkenmark J Rockström . Building water resilience in the face of global change: from a blue-only to a green-blue water approach to land-water management. Journal of Water Resources Planning and Management, 2010, 136(6): 606–610 https://doi.org/10.1061/(ASCE)WR.1943-5452.0000118
24
J F, Schyns A Y, Hoekstra M J, Booij R J, Hogeboom M M Mekonnen . Limits to the world’s green water resources for food, feed, fiber, timber, and bioenergy. Proceedings of the National Academy of Sciences of the United States of America, 2019, 116(11): 4893–4898 https://doi.org/10.1073/pnas.1817380116
25
A Y, Hoekstra M M Mekonnen . The water footprint of humanity. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(9): 3232–3237 https://doi.org/10.1073/pnas.1109936109
26
J, Liu A J B, Zehnder H Yang . Global consumptive water use for crop production: the importance of green water and virtual water. Water Resources Research, 2009, 45(5): 2007WR006051 https://doi.org/10.1029/2007WR006051
27
L, Jin W Young . Water use in agriculture in China: importance, challenges, and implications for policy. Water Policy, 2001, 3(3): 215–228 https://doi.org/10.1016/S1366-7017(01)00015-0
28
M I, Brunner M, Zappa M Stähli . Scale matters: effects of temporal and spatial data resolution on water scarcity assessments. Advances in Water Resources, 2019, 123: 134–144 https://doi.org/10.1016/j.advwatres.2018.11.013
29
A V, Pastor F, Ludwig H, Biemans H, Hoff P Kabat . Accounting for environmental flow requirements in global water assessments. Hydrology and Earth System Sciences, 2014, 18(12): 5041–5059 https://doi.org/10.5194/hess-18-5041-2014
30
J, Jägermeyr A, Pastor H, Biemans D Gerten . Reconciling irrigated food production with environmental flows for Sustainable Development Goals implementation. Nature Communications, 2017, 8(1): 15900 https://doi.org/10.1038/ncomms15900
31
A V, Pastor A, Palazzo P, Havlik H, Biemans Y, Wada M, Obersteiner P, Kabat F Ludwig . The global nexus of food–trade–water sustaining environmental flows by 2050. Nature Sustainability, 2019, 2(6): 499–507 https://doi.org/10.1038/s41893-019-0287-1
32
Y, Li K, Guan G D, Schnitkey E, DeLucia B Peng . Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Global Change Biology, 2019, 25(7): 2325–2337 https://doi.org/10.1111/gcb.14628
33
Y, Wada D, Wisser M F P Bierkens . Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources. Earth System Dynamics, 2014, 5(1): 15–40
34
P A, Dirmeyer X, Gao M, Zhao Z, Guo T, Oki N Hanasaki . GSWP-2: Multimodel analysis and implications for our perception of the land surface. Bulletin of the American Meteorological Society, 2006, 87(10): 1381–1398
35
G P, Weedon S, Gomes P, Viterbo W J, Shuttleworth E, Blyth H, Österle J C, Adam N, Bellouin O, Boucher M Best . Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. Journal of Hydrometeorology, 2011, 12(5): 823–848 https://doi.org/10.1175/2011JHM1369.1
36
G P, Weedon G, Balsamo N, Bellouin S, Gomes M J, Best P Viterbo . The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA‐Interim reanalysis data. Water Resources Research, 2014, 50(9): 7505–7514 https://doi.org/10.1002/2014WR015638
37
J, Sheffield G, Goteti E F Wood . Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 2006, 19(13): 3088–3111 https://doi.org/10.1175/JCLI3790.1
38
F T, Portmann S, Siebert P Döll . MIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: a new high-resolution data set for agricultural and hydrological modeling. Global Biogeochemical Cycles, 2010, 24(1): 2008GB003435 https://doi.org/10.1029/2008GB003435
39
L, Zhang F, Chen Y Lei . Climate change and shifts in cropping systems together exacerbate China’s water scarcity. Environmental Research Letters, 2020, 15(10): 104060 https://doi.org/10.1088/1748-9326/abb1f2
40
M M, Mekonnen A Y Hoekstra . Four billion people facing severe water scarcity. Science Advances, 2016, 2(2): e1500323 https://doi.org/10.1126/sciadv.1500323
41
M, Tuninetti S, Tamea C Dalin . Water debt indicator reveals where agricultural water use exceeds sustainable levels. Water Resources Research, 2019, 55(3): 2464–2477 https://doi.org/10.1029/2018WR023146
42
H, Xu M Wu . A first estimation of county-based green water availability and its implications for agriculture and bioenergy production in the United States. Water, 2018, 10(2): 148 https://doi.org/10.3390/w10020148
43
W, Liu H, Yang C, Folberth X, Wang Q, Luo R Schulin . Global investigation of impacts of PET methods on simulating crop-water relations for maize. Agricultural and Forest Meteorology, 2016, 221: 164–175 https://doi.org/10.1016/j.agrformet.2016.02.017
