{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:23:21Z","timestamp":1783596201825,"version":"3.55.0"},"reference-count":60,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,11]],"date-time":"2019-12-11T00:00:00Z","timestamp":1576022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41561144013, 41761144064 and 4171101213"],"award-info":[{"award-number":["41561144013, 41761144064 and 4171101213"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R\uff06D Program of China","award":["2016YFA0600304"],"award-info":[{"award-number":["2016YFA0600304"]}]},{"name":"International Partnership Program of Chinese Academy of Sciences","award":["121311KYSB20170004"],"award-info":[{"award-number":["121311KYSB20170004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Precipitation plays an important role in the food production of Southern Africa. Understanding the spatial and temporal variations of precipitation is helpful for improving agricultural management and flood and drought risk assessment. However, a comprehensive precipitation pattern analysis is challenging in sparsely gauged and underdeveloped regions. To solve this problem, Version 7 Tropical Rainfall Measuring Mission (TRMM) precipitation products and Google Earth Engine (GEE) were adopted in this study for the analysis of spatiotemporal patterns of precipitation in the Zambezi River Basin. The Kendall\u2019s correlation and sen\u2019s Slop reducers in GEE were used to examine precipitation trends and magnitude, respectively, at annual, seasonal and monthly scales from 1998 to 2017. The results reveal that 10% of the Zambezi River basin showed a significant decreasing trend of annual precipitation, while only 1% showed a significant increasing trend. The rainy-season precipitation appeared to have a dominant impact on the annual precipitation pattern. The rainy-season precipitation was found to have larger spatial, temporal and magnitude variation than the dry-season precipitation. In terms of monthly precipitation, June to September during the dry season were dominated by a significant decreasing trend. However, areas presenting a significant decreasing trend were rare (&lt;12% of study area) and scattered during the rainy-season months (November to April of the subsequent year). Spatially, the highest and lowest rainfall regions were shifted by year, with extreme precipitation events (highest and lowest rainfall) occurring preferentially over the northwest side rather than the northeast area of the Zambezi River Basin. A \u201cdry gets dryer, wet gets wetter\u201d (DGDWGW) pattern was also observed over the study area, and a suggestion on agriculture management according to precipitation patterns is provided in this study for the region. This is the first study to use long-term remote sensing data and GEE for precipitation analysis at various temporal scales in the Zambezi River Basin. The methodology proposed in this study is helpful for the spatiotemporal analysis of precipitation in developing countries with scarce gauge stations, limited analytic skills and insufficient computation resources. The approaches of this study can also be operationally applied to the analysis of other climate variables, such as temperature and solar radiation.<\/jats:p>","DOI":"10.3390\/rs11242977","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T03:20:16Z","timestamp":1576120816000},"page":"2977","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Spatiotemporal Analysis of Precipitation in the Sparsely Gauged Zambezi River Basin Using Remote Sensing and Google Earth Engine"],"prefix":"10.3390","volume":"11","author":[{"given":"Hongwei","family":"Zeng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5546-365X","authenticated-orcid":false,"given":"Bingfang","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Geography, the Ohio State University, Columbus, OH 43202, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1758-8763","authenticated-orcid":false,"given":"Fuyou","family":"Tian","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3637-3509","authenticated-orcid":false,"given":"Elijah","family":"Phiri","sequence":"additional","affiliation":[{"name":"Department of Soil Science, School of Agricultural Sciences, University of Zambia, Lusaka 32379, Zambia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2173-0072","authenticated-orcid":false,"given":"Walter","family":"Musakwa","sequence":"additional","affiliation":[{"name":"Town and Regional Planning Department, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Mashonjowa","sequence":"additional","affiliation":[{"name":"Physics Department, University of Zimbabwe, Mt. Pleasant, Harare P.O. Box MP167, Zimbabwe"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1126\/science.1092958","article-title":"Global Food Security: Challenges and Policies","volume":"302","author":"Rosegrant","year":"2003","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s10113-015-0761-x","article-title":"Climate change, food security, and livelihoods in sub-Saharan Africa","volume":"16","author":"Smit","year":"2016","journal-title":"Reg. Environ. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.agee.2008.01.007","article-title":"Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: An essential first step in adapting to future climate change?","volume":"126","author":"Cooper","year":"2008","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s11069-011-0064-6","article-title":"Extreme weather and economic well-being in rural Mozambique","volume":"66","author":"Matyas","year":"2013","journal-title":"Nat. Hazards"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1175\/WCAS-D-13-00012.1","article-title":"Relating Rainfall Patterns to Agricultural Income: Implications for Rural Development in Mozambique","volume":"6","author":"Silva","year":"2013","journal-title":"Weather Clim. Soc."},{"key":"ref_6","first-page":"1123","article-title":"Recent change of the global monsoon precipitation (1979\u20132008)","volume":"39","author":"Wang","year":"2012","journal-title":"ClDy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s12040-013-0395-7","article-title":"Trend analysis and change point detection of annual and seasonal precipitation and temperature series over southwest Iran","volume":"123","author":"Zarenistanak","year":"2014","journal-title":"J. Earth Syst. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.atmosres.2013.10.012","article-title":"Seasonal and annual precipitation time series trend analysis in North Carolina, United States","volume":"137","author":"Sayemuzzaman","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1002\/asl.602","article-title":"Precipitation trend analysis of Sindh River basin, India, from 102-year record (1901\u20132002)","volume":"17","author":"Gajbhiye","year":"2016","journal-title":"Atmos. Sci. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.gloplacha.2017.12.014","article-title":"Rainfall over the African continent from the 19th through the 21st century","volume":"165","author":"Nicholson","year":"2018","journal-title":"Glob. Planet. Chang."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.jhydrol.2005.11.041","article-title":"Comparison of satellite rainfall data with observations from gauging station networks","volume":"327","author":"Hughes","year":"2006","journal-title":"J. Hydrol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.1175\/JHM-D-12-07.1","article-title":"Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling","volume":"13","author":"Rasmussen","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1016\/j.jhydrol.2016.08.010","article-title":"Effects of different regional climate model resolution and forcing scales on projected hydrologic changes","volume":"541","author":"Mendoza","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/2017RG000574","article-title":"A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons","volume":"56","author":"Sun","year":"2018","journal-title":"Rev. Geophys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1175\/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2","article-title":"The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979\u2013Present)","volume":"4","author":"Adler","year":"2003","journal-title":"J. Hydrometeorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-13-00068.1","article-title":"PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies","volume":"96","author":"Ashouri","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1175\/JTECH-D-11-00103.1","article-title":"An Overview of the Global Historical Climatology Network-Daily Database","volume":"29","author":"Menne","year":"2012","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1175\/BAMS-D-13-00164.1","article-title":"The Global Precipitation Measurement Mission","volume":"95","author":"Hou","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"95","DOI":"10.3354\/cr01489","article-title":"Spatial distribution of secular trends in annual and seasonal precipitation over Pakistan","volume":"74","author":"Ahmed","year":"2017","journal-title":"Clim. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1007\/s10712-017-9416-4","article-title":"Global Precipitation: Means, Variations and Trends During the Satellite Era (1979\u20132014)","volume":"38","author":"Adler","year":"2017","journal-title":"Surv. Geophys."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Gu, G., Adler, R.F., and Huffman, G. (2015). Long-Term Changes\/Trends in Surface Temperature and Precipitation During the Satellite Era (1979\u20132012), Springer.","DOI":"10.1007\/s00382-015-2634-x"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1002\/asl.631","article-title":"Decadal trends of the annual amplitude of global precipitation","volume":"17","author":"Wang","year":"2016","journal-title":"Atmos. Sci. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3009","DOI":"10.1007\/s00382-012-1443-8","article-title":"Interdecadal variability\/long-term changes in global precipitation patterns during the past three decades: Global warming and\/or pacific decadal variability?","volume":"40","author":"Gu","year":"2013","journal-title":"Clim. Dyn."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1175\/BAMS-D-17-0065.1","article-title":"Global Precipitation Trends across Spatial Scales Using Satellite Observations","volume":"99","author":"Nguyen","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2016.02.016","article-title":"Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine","volume":"185","author":"Dong","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.isprsjprs.2017.01.019","article-title":"Automated cropland mapping of continental Africa using Google Earth Engine cloud computing","volume":"126","author":"Xiong","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, X., Wu, B., Ponce-Campos, E.G., Zhang, M., Chang, S., and Tian, F. (2018). Mapping up-to-Date Paddy Rice Extent at 10 M Resolution in China through the Integration of Optical and Synthetic Aperture Radar Images. Remote Sens., 10.","DOI":"10.3390\/rs10081200"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.envsoft.2015.06.011","article-title":"A novel approach to mapping land conversion using Google Earth with an application to East Africa","volume":"72","author":"Jacobson","year":"2015","journal-title":"Environ. Model. Softw."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Long, T., Zhang, Z., He, G., Jiao, W., Tang, C., Wu, B., Zhang, X., Wang, G., and Yin, R. (2019). 30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine. Remote Sens., 11.","DOI":"10.3390\/rs11050489"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_35","first-page":"199","article-title":"Multitemporal settlement and population mapping from Landsat using Google Earth Engine","volume":"35","author":"Patel","year":"2015","journal-title":"IJAEO"},{"key":"ref_36","first-page":"773","article-title":"Assessing future risks to agricultural productivity, water resources and food security: How can remote sensing help?","volume":"78","author":"Thenkabail","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_37","unstructured":"WorldBank (2010). The Zambezi River Basin: A Multi-Sector Investment Opportunities Analysis (Vol. 4): Modeling, Analysis, and Input Data, World Bank. Available online: http:\/\/documents.worldbank.org\/curated\/en\/599191468203672747\/Modeling-analysis-and-input-data."},{"key":"ref_38","first-page":"3679","article-title":"Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium","volume":"30","author":"Thenkabail","year":"2009","journal-title":"IJRS"},{"key":"ref_39","first-page":"114","article-title":"A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing","volume":"11","author":"Biradar","year":"2009","journal-title":"IJAEO"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"489","DOI":"10.5194\/hess-16-489-2012","article-title":"Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin","volume":"16","author":"Matos","year":"2012","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1760","DOI":"10.1175\/JHM-D-12-032.1","article-title":"Validation of Satellite-Based Precipitation Products over Sparsely Gauged African River Basins","volume":"13","author":"Thiemig","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Poortinga, A., Clinton, N., Saah, D., Cutter, P., Chishtie, F., Markert, K.N., Anderson, E.R., Troy, A., Fenn, M., and Tran, L.H. (2018). An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale. Remote Sens., 10.","DOI":"10.3390\/rs10050760"},{"key":"ref_43","unstructured":"Prokhorov, A.J.O. (2001). Kendall Coefficient of Rank Correlation. Encyclopedia of Measurement and Statistics, Sage."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the Regression Coefficient Based on Kendall\u2019s Tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Amer. Stat. Assoc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1111\/j.1752-1688.2003.tb03677.x","article-title":"Long term trends of annual and monthly precipitation in Japan1","volume":"39","author":"Yue","year":"2003","journal-title":"JAWRA J. Am. Water Resour. Assoc."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1007\/s00704-015-1422-1","article-title":"Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe","volume":"124","author":"Muchuru","year":"2016","journal-title":"Theor. Appl. Climatol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1080\/02626667.2014.983519","article-title":"Rainfall characteristics and their implications for rain-fed agriculture: A case study in the Upper Zambezi River Basin","volume":"61","author":"Beyer","year":"2016","journal-title":"Hydrol. Sci. J."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1038\/nature11575","article-title":"Little change in global drought over the past 60 years","volume":"491","author":"Sheffield","year":"2012","journal-title":"Nature"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1126\/science.1212222","article-title":"Ocean Salinities Reveal Strong Global Water Cycle Intensification During 1950 to 2000","volume":"336","author":"Durack","year":"2012","journal-title":"Science"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1038\/ngeo2247","article-title":"Global assessment of trends in wetting and drying over land","volume":"7","author":"Greve","year":"2014","journal-title":"Nat. Geosci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.1002\/joc.5863","article-title":"\u201cDry gets drier, wet gets wetter\u201d: A case study over the arid regions of central Asia","volume":"39","author":"Hu","year":"2019","journal-title":"Int. J. Climatol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1002\/joc.4752","article-title":"Rainfall variability over Zimbabwe and its relation to large-scale atmosphere\u2013ocean processes","volume":"37","author":"Mamombe","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"199","DOI":"10.3354\/cr026199","article-title":"Dry spell frequencies and their variability over southern Africa","volume":"26","author":"Muhammad","year":"2004","journal-title":"Clim. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1002\/(SICI)1097-0088(199702)17:2<117::AID-JOC84>3.0.CO;2-O","article-title":"The relationship of the el ni\u00f1o\u2013southern oscillation to african rainfall","volume":"17","author":"Nicholson","year":"1997","journal-title":"Int. J. Climatol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1002\/joc.1062","article-title":"A new analysis of variability and predictability of seasonal rainfall of central southern Africa for 1950\u201394","volume":"24","author":"Mwale","year":"2004","journal-title":"Int. J. Climatol."},{"key":"ref_56","unstructured":"Williams, C.J.R., and Kniveton, D.R. (2011). Understanding the Large Scale Driving Mechanisms of Rainfall Variability over Central Africa. African Climate and Climate Change: Physical, Social and Political Perspectives, Springer Netherlands."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"9","DOI":"10.5334\/jors.197","article-title":"Tethys\u2013A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals","volume":"6","author":"Li","year":"2018","journal-title":"J. Open Res. Softw."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1016\/j.agwat.2010.01.008","article-title":"Water resources and water use efficiency in the North China Plain: Current status and agronomic management options","volume":"97","author":"Fang","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1002\/joc.1677","article-title":"Climate, agricultural production and hydrological balance in the North China Plain","volume":"28","author":"Wang","year":"2008","journal-title":"Int. J. Climatol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.5194\/hess-19-1521-2015","article-title":"A global data set of the extent of irrigated land from 1900 to 2005","volume":"19","author":"Siebert","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/24\/2977\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:41:32Z","timestamp":1760190092000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/24\/2977"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,11]]},"references-count":60,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["rs11242977"],"URL":"https:\/\/doi.org\/10.3390\/rs11242977","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,11]]}}}