# Rio Grande 500 Year Riverflow and Precipitation Reconstructions #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original reference when using these data, # plus the Online Resource and date accessed. # # Online_Resource: http://hurricane.ncdc.noaa.gov/pls/paleox/f?p=519:1:::::P1_STUDY_ID:14249 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/northamerica/riogrande2013precip.txt # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions #-------------------- # Contribution_Date # Date: 2013-04-16 #-------------------- # Title # Study_Name: Rio Grande 500 Year Riverflow and Precipitation Reconstructions #-------------------- # Investigators # Investigators: Woodhouse, C.A.; Meko, D.M.; Griffin, D.; Castro, C.L. #-------------------- # Description_and_Notes # Description: Tree Ring-based reconstructions of upper and lower Rio Grande Basin precipitation # and riverflow for the past 500 years. Reconstructed Rio Grande Water Year Flow at Del Norte, CO, # in both acre feet and cubic meters per second, plus Reconstructed June-July total precipitation # in millimeters, are presented. #-------------------- # Publication # Authors: Woodhouse, C.A., D.M. Meko, D. Griffin, and C.L. Castro # Published_Date_or_Year: 2013-02-08 # Published_Title: Tree rings and multiseason drought variability in the lower Rio Grande Basin, USA. # Journal_Name: Water Resources Research # Volume: 49 # Edition: # Issue: 2 # Pages: 844-850 # DOI: 10.1002/wrcr.20098 # Abstract: Agriculture and ranching in semiarid regions often rely on local precipitation during the growing season as well as streamflow from runoff in distant headwaters. Where snowpack and reservoir storage are important, this pattern of reliance leads to vulnerability to multiseason drought. The lower Rio Grande basin in New Mexico, used as a case study here, has experienced drought conditions over the past 12 years characterized both by low local summer monsoon precipitation and by reduced availability of surface water supplies from the upper Rio Grande. To place this drought in a long-term context, we evaluate the covariability of local warm-season and remote cool-season hydroclimate over both the modern period and past centuries. We draw on a recently developed network of tree-ring data that allows an assessment of preinstrumental warm-season variations in precipitation over the southwest. Both instrumental and paleoclimatic data suggest that low runoff followed by a dry monsoon is not unusual, although over the full reconstruction period (1659-2008), years with wet or dry conditions shared in both seasons do not occur significantly more often than unshared conditions. Low flows followed by dry monsoon conditions were most persistent in the 1770s and 1780s; other notable periods of shared seasonal droughts occurred in the 1660s and 1950s. The recent drought does not yet appear to be unusually severe in either the instrumental or paleoclimatic context. #-------------------- # Publication # Authors: Connie A. Woodhouse, David W. Stahle, José Villanueva Díaz # Published_Date_or_Year: 2012-03-07 # Published_Title: Rio Grande and Rio Conchos water supply variability over the past 500 years # Journal_Name: Climate Research # Volume: 51 # Edition: # Issue: 2 # Pages: 125-136 # DOI: 10.3354/cr01059 # Abstract: The Rio Grande is a major source of water for parts of Mexico and the USA. The 2 main source regions for the Rio Grande system are the San Juan Mountains of the southern Rocky Mountains and the Sierra Madre Occidental in Mexico, which is the headwaters for the Rio Conchos, the largest tributary of the Rio Grande. Precipitation and streamflow from these 2 source regions are largely independent of each other; winter snowpack is the dominant contributor to the annual streamflow north of the USA-Mexico border, and the North American monsoon is a key factor in the Rio Conchos basin. Reconstructions of water year (October-September) streamflow for a gauge in the upper Rio Grande, 1508-2002, and of October-July precipitation in the Rio Conchos watershed region, 1649-1993, also indicate a lack of correlation between the 2 basins over century time scales. Despite this lack of correlation, periods of concurrent multiyear drought have occurred over the past 4 centuries, most notably in the 1770s, 1890s and 1950s. These rare concurrent droughts in the upper Rio Grande and Rio Conchos source regions may arise from large-scale forcing out of the Pacific Ocean and will be relevant to the binational planning of these water resources, which serve a large and growing population of users. #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 0823090 #------------------ # Funding_Agency # Funding_Agency_Name: US Envronmental Protection Agency # Grant: STAR Fellowship #------------------ # Site_Information # Site_Name: Lower Rio Grande Region # Location: North America>United States Of America>New Mexico # Country: United States Of America # Northernmost_Latitude: 34.12 # Southernmost_Latitude: 31.75 # Easternmost_Longitude: -106.00 # Westernmost_Longitude: -108.12 # Elevation: m #------------------ # Data_Collection # Collection_Name: RioGrande2013precip # Earliest_Year: 1659 # Most_Recent_Year: 2008 # Time_Unit: AD # Core_Length: m # Notes: #------------------ # Chronology: # # # #---------------- # Variables # # Data variables follow (have no #) # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ## age_AD age, , , AD, , , , ,N ## precip-JJ Precipitation, , , mm, June-July, , , observed, N ## preciprec-JJ Precipitation, , , mm, June-July, , , reconstructed, N # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: -9999 age_AD precip-JJ preciprec-JJ 1659 -9999 42.598 1660 -9999 34.753 1661 -9999 71.094 1662 -9999 78.125 1663 -9999 69.408 1664 -9999 27.956 1665 -9999 39.852 1666 -9999 55.71 1667 -9999 33.932 1668 -9999 32.427 1669 -9999 42.212 1670 -9999 58.621 1671 -9999 43.487 1672 -9999 52.896 1673 -9999 28.855 1674 -9999 62.025 1675 -9999 38.955 1676 -9999 76.196 1677 -9999 75.421 1678 -9999 65.605 1679 -9999 50.402 1680 -9999 56.73 1681 -9999 33.117 1682 -9999 35.799 1683 -9999 69.579 1684 -9999 72.977 1685 -9999 46.152 1686 -9999 45.328 1687 -9999 33.806 1688 -9999 63.803 1689 -9999 73.082 1690 -9999 59.434 1691 -9999 41.329 1692 -9999 59.68 1693 -9999 36.035 1694 -9999 58.043 1695 -9999 46.875 1696 -9999 29.48 1697 -9999 62.396 1698 -9999 54.218 1699 -9999 51.03 1700 -9999 61.506 1701 -9999 55.296 1702 -9999 64.177 1703 -9999 74.871 1704 -9999 33.014 1705 -9999 52.459 1706 -9999 51.379 1707 -9999 37.527 1708 -9999 38.895 1709 -9999 57.669 1710 -9999 72.056 1711 -9999 33.198 1712 -9999 47.042 1713 -9999 55.512 1714 -9999 68.121 1715 -9999 33.181 1716 -9999 75.484 1717 -9999 63.833 1718 -9999 42.78 1719 -9999 34.603 1720 -9999 70.913 1721 -9999 70.707 1722 -9999 46.835 1723 -9999 54.86 1724 -9999 81.853 1725 -9999 67.279 1726 -9999 57.199 1727 -9999 18.843 1728 -9999 55.852 1729 -9999 37.11 1730 -9999 58.032 1731 -9999 42.841 1732 -9999 48.898 1733 -9999 41.106 1734 -9999 70.437 1735 -9999 36.302 1736 -9999 53.339 1737 -9999 36.431 1738 -9999 60.025 1739 -9999 31.036 1740 -9999 42.476 1741 -9999 47.675 1742 -9999 48.974 1743 -9999 75.104 1744 -9999 62.952 1745 -9999 29.943 1746 -9999 63.261 1747 -9999 52.616 1748 -9999 42.112 1749 -9999 43.429 1750 -9999 63.388 1751 -9999 51.203 1752 -9999 34.94 1753 -9999 62.861 1754 -9999 54.235 1755 -9999 50.385 1756 -9999 41.495 1757 -9999 70.163 1758 -9999 51.249 1759 -9999 44.795 1760 -9999 32.693 1761 -9999 65.365 1762 -9999 54.847 1763 -9999 35.088 1764 -9999 83.717 1765 -9999 52.432 1766 -9999 61.395 1767 -9999 85.786 1768 -9999 45.308 1769 -9999 68.917 1770 -9999 37.963 1771 -9999 67.921 1772 -9999 38.503 1773 -9999 45.507 1774 -9999 48.986 1775 -9999 48.568 1776 -9999 48.356 1777 -9999 35.326 1778 -9999 58.473 1779 -9999 31.71 1780 -9999 50.351 1781 -9999 48.939 1782 -9999 54.107 1783 -9999 47.472 1784 -9999 60.84 1785 -9999 50.815 1786 -9999 42.203 1787 -9999 59.839 1788 -9999 62.808 1789 -9999 32.745 1790 -9999 76.727 1791 -9999 51.499 1792 -9999 42.471 1793 -9999 96.001 1794 -9999 63.947 1795 -9999 42.984 1796 -9999 52.775 1797 -9999 43.99 1798 -9999 41.156 1799 -9999 62.005 1800 -9999 61.592 1801 -9999 50.422 1802 -9999 45.458 1803 -9999 65.254 1804 -9999 42.422 1805 -9999 43.751 1806 -9999 53.785 1807 -9999 45.176 1808 -9999 51.898 1809 -9999 57.713 1810 -9999 59.896 1811 -9999 71.328 1812 -9999 40.188 1813 -9999 51.301 1814 -9999 51.179 1815 -9999 62.689 1816 -9999 58.411 1817 -9999 29.878 1818 -9999 41.725 1819 -9999 54.434 1820 -9999 78.592 1821 -9999 18.968 1822 -9999 48.983 1823 -9999 44.492 1824 -9999 40.342 1825 -9999 41.682 1826 -9999 47.234 1827 -9999 79.066 1828 -9999 47.828 1829 -9999 58.716 1830 -9999 73.464 1831 -9999 58.445 1832 -9999 56.514 1833 -9999 41.117 1834 -9999 43.361 1835 -9999 64.568 1836 -9999 45.785 1837 -9999 39.448 1838 -9999 46.463 1839 -9999 69.78 1840 -9999 49.989 1841 -9999 39.04 1842 -9999 65.066 1843 -9999 42.171 1844 -9999 65.439 1845 -9999 75.826 1846 -9999 48.98 1847 -9999 63.531 1848 -9999 64.601 1849 -9999 54.005 1850 -9999 30.532 1851 -9999 46.496 1852 -9999 59.958 1853 -9999 49.064 1854 -9999 58.667 1855 -9999 35.256 1856 -9999 52.864 1857 -9999 44.64 1858 -9999 68.349 1859 -9999 52.541 1860 -9999 42.565 1861 -9999 50.953 1862 -9999 36.928 1863 -9999 42.029 1864 -9999 52.215 1865 -9999 42.188 1866 -9999 67.938 1867 -9999 50.545 1868 -9999 64.494 1869 -9999 44.674 1870 -9999 80.02 1871 -9999 67.241 1872 -9999 38.542 1873 -9999 34.951 1874 -9999 42.107 1875 -9999 69.002 1876 -9999 47.496 1877 -9999 36.136 1878 -9999 59.192 1879 -9999 47.421 1880 -9999 49.248 1881 -9999 52.936 1882 -9999 41.679 1883 -9999 66.501 1884 -9999 33.316 1885 -9999 56.186 1886 -9999 46.751 1887 -9999 56.842 1888 -9999 31.844 1889 -9999 52.867 1890 -9999 59.162 1891 -9999 35.672 1892 -9999 37.551 1893 -9999 43.772 1894 -9999 42.797 1895 79.502 68.42 1896 70.358 53.308 1897 57.404 44.309 1898 92.456 88.991 1899 67.818 77.702 1900 29.718 35.835 1901 47.244 50.295 1902 27.686 41.467 1903 49.276 33.419 1904 31.242 49.477 1905 57.658 46.067 1906 33.782 50.48 1907 38.862 62.629 1908 46.736 58.805 1909 44.196 33.505 1910 37.592 49.634 1911 99.314 64.283 1912 67.818 59.029 1913 43.942 35.161 1914 120.904 83.373 1915 78.486 54.15 1916 42.418 43.223 1917 27.94 44.44 1918 44.704 58.395 1919 71.628 82.925 1920 51.562 44.432 1921 85.344 80.067 1922 30.734 35.053 1923 33.02 38.39 1924 58.166 55.129 1925 55.372 43.737 1926 49.53 49.019 1927 55.372 59.627 1928 26.162 41.732 1929 68.072 64.001 1930 60.706 54.444 1931 54.864 55.806 1932 56.134 63.735 1933 87.122 66.467 1934 25.146 32.702 1935 25.146 54.171 1936 35.56 51.095 1937 41.656 42.787 1938 76.962 86.744 1939 38.354 34.062 1940 52.832 52.264 1941 57.912 60.625 1942 27.94 40.553 1943 64.262 65.846 1944 44.958 51.465 1945 29.718 53.535 1946 42.672 46.863 1947 26.416 44.011 1948 39.37 38.475 1949 55.118 54.144 1950 73.914 62.48 1951 21.082 42.702 1952 50.8 32.614 1953 50.038 48.929 1954 32.004 32.137 1955 66.802 59.423 1956 37.084 35.806 1957 54.356 56.351 1958 43.434 43.757 1959 40.132 41.718 1960 62.738 50.022 1961 42.926 43.627 1962 72.898 63.712 1963 26.924 45.099 1964 37.846 48.34 1965 49.276 53.38 1966 70.612 65.779 1967 58.674 69.083 1968 53.848 59.448 1969 50.546 46.069 1970 51.562 60.258 1971 38.354 56.608 1972 59.944 50.545 1973 58.166 63.226 1974 57.658 46.373 1975 51.308 42.263 1976 54.356 50.63 1977 58.166 53.726 1978 35.306 44.42 1979 57.658 52.951 1980 19.304 33.21 1981 65.024 57.098 1982 32.766 46.891 1983 34.544 43.007 1984 67.056 57.569 1985 47.752 42.95 1986 97.79 93.253 1987 51.816 34.157 1988 66.802 83.51 1989 56.642 31.482 1990 58.928 60.155 1991 64.77 69.677 1992 48.514 51.166 1993 39.624 50.789 1994 31.242 38.557 1995 36.576 50.171 1996 85.344 61.685 1997 63.246 34.71 1998 66.04 66.886 1999 77.978 92.006 2000 73.406 56.377 2001 45.72 37.175 2002 44.958 39.833 2003 26.162 32.594 2004 40.132 48.424 2005 14.732 32.631 2006 80.264 50.602 2007 53.086 39.991 2008 92.71 77.871