References and Publications

Brito-Castillo, L., A. Leyva-Contreras, A.V. Douglas, D. Lluch-Belda, 2002. Pacific decadal oscillation and the filled capacity of dams on the rivers of the Gulf of California continental watershed. Atmosfera (15), 121-138.

Gochis, D.J. and W. J. Shuttleworth, 2003a: The hydrometeorological response of the modeled North American Monsoon to convective parameterization. In Press, J. of Hydrometeorology.

Gochis, D.J., J.-C. Leal, C.J. Watts, and W.J. Shuttleworth, 2003b: Preliminary diagnostics from a new event-based precipitation monitoring system in support of NAME. In Press, J. Hydrometeorology. 

AcknowledgementsSupport for this work was provided in part by the NOAA Joint CLIVAR/PACS-GEWEX/GAPP North American Warm Season Precipitation Initiative: Contract No. NA16GP2002 and by the Advanced Study Program at the National Center for Atmospheric Research.

1NCAR/ASP/RAP (E-mail: gochis@rap.ucar.edu); 2IMADES, Hermosillo, Son. MX; 3HWR, Univ. Arizona; 4ITSON, Obregon, Son. MX

ABSTRACT

David J. Gochis1, Juan-Carlos Leal2, W. James Shuttleworth3, Christopher J. Watts2, Jaime Garatuza Payan4

The mountain and coastal plain regions of the northwestern Mexico lie under the influence of the North American Monsoon System (NAMS). Recent analyses have shown this region to exhibit among the highest interannual variance in precipitation and in streamflow in the world. However, no clear relationship between large-scale teleconnective forcing (such as sea-surface temperatures) and regional hydrometeorology has yet been established. Precipitation characteristics such as intensity-frequency-duration relationships from a new event-based raingage network are presented. Correlations between the various precipitation characteristics and streamgage measurements in 15 unregulated basins in western Mexico are explored. The relationship between topography and precipitation structure are also be examined. In future studies, particular attention will be focused on the relationship between catchment topographic features and soil structure (e.g. soil type and depth) and estimates of runoff fractions.

The North American Monsoon Region:Selected Test Basins

Normalized Monthly Average Flow Volumes

05

10152025303540

May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr

Month

% o

f A

nn

. A

ve

rag

e

Coefficient of Variation of Monthly Flow Volumes

00.5

11.5

22.5

33.5

44.5

M ay Jun Jul Aug Sept Oct Nov Dec Jan Feb M ar Apr

Month

Co

eff

. o

f V

ari

atio

n Batopilas

Sen Pedro del Conchos

Mayo

Chinipas

Urique

Piaxtla

San Lorenzo

Presidio

Sextin

Choix

Tamazula

Badiraguato

Humaya, La Huerta

Acaponeta

Baluarte

Normalized Monthly Maximum Flow Volumes

0

50

100

150

200

May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr

Month

% o

f A

nn

. A

ve

rag

e

Principal Components Analysis (PCA)Lag 1 Ranked Autocorrelations for

Monthly Streamflow Volume Anomalies

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan

Month

Co

rre

l. C

oe

ff.

Batopilas

San Pedro del Conchos

Mayo

Chinipas

Urique

Piaxtla

San Lorenzo

Presidio

Sextin

Choix

Tamazula

Badiraguato

Humaya

Acaponeta

Baluarte II

JASRunoff Coefficient Std Range

Basin Area (Q/P)

San Pedro del Conchos 9405 0.09 0.06 0.21Chinipas 5098 0.27 0.12 0.67Mayo 7510 0.18 0.09 0.39Urique 4000 0.13 0.08 0.43Batopilas 2033 0.22 0.10 0.36Choix 1403 0.34 0.15 0.71Sextin 4911 0.21 0.12 0.42Humaya 6149 0.23 0.10 0.39Badiraguato 1018 0.30 0.19 1.15Tamazula 2241 0.40 0.20 1.07San Lorenzo 8919 0.23 0.13 0.58Piaxtla 6166 0.33 0.15 0.84Presidio 5614 0.24 0.10 0.46Baluarte 4635 0.43 0.17 0.72Acaponeta 5092 0.34 0.11 0.47

Runoff Coefficient Analysis

Rainfall Runoff Correlation Structure

The Streamflow Regime in NW Mexico

Precipitation Characteristics in the NAM Region

Elevation Bands Network B1 B2 B3 B4 B5 B6

Elevation Band Interval (m) 0-500 500-1000 1000-1500 1500-2000 2000-2500 2500-3000

Total Number of Gages 50 16 10 1 10 11 2

Percent of Network (%) 32 20 2 20 22 4

# Gages Rporting (2002) 47 14 10 1 9 11 2

Average % of Wet-Days 51 38 51 71 61 59 54

Std. Dev. % of Wet-Days 15 8 11 n/a 19 10 2

Avg. Intensity (mm/hr) 2.7 3.2 2.3 3.2 2.4 2.3 2.5

Avg. Max. Intensity 28.2 35.4 29.3 27.9 22.2 25.3 15.2

Std. Dev. Max. Intensity 13.7 15.2 10.3 n/a 10.2 15.5 5.4

Abs. Max. Intensity 67.3 67.3 41.7 27.9 40.6 54.1 19.1

The core region of the North American Monsoon region is characterized by steep topographic and precipitation gradients, which, in turn, result in strong gradients in vegetation. For the streamflow analysis portion of this study we have selected 15 basins which drain the Sierra Madre Occidental mountains in western Mexico (2 of which drain to the east). Drainage areas range between 1,000 and 10,000 sq. km. All basins are also unregulated by impoundments or large diversions with the exception of the San Lorenzo basin (#11) Other basin characteristics are provided in the Table 1.

Table 1Drainage Drainage Gage Gage Period of Mean Annual Coefficient of

Station River Basin Area Location Location Record Discaharge (MAQ) Variation MAQ

(sq. km ) (deg) (deg) (10^3 m 3)

1. Villalba San Pedro del Conchos Conchos* 9405 105 46 40 27 59 10 1938-1990 411401 0.637126562

2. Chinipas Chinipas/Oteros Fuerte 5098 108 32 30 27 25 00 1965-1998 1023985 0.50

3. San Bernardo Mayo Mayo 7510 108 52 55 27 24 45 1960-1999 1003542 0.40

4. Urique Urique Fuerte 4000 107 50 20 27 18 10 1968-1999 439165 0.546308563

5. Batopilas Batopilas Fuerte 2033 107 44 15 27 01 20 1982-1997 372859 0.382620448

6. Choix Choix Fuerte 1403 108 19 45 26 44 10 1955-1998 295679 0.373574918

7. Sardinas Sextin or del Oro Aguanaval* 4911 105 34 12 26 05 00 1970-1994 524074 0.609800489

8. La Huerta Humaya Culiacan 6149 106 42 00 25 22 10 1969-1999 1120591 0.50

9. Badiraguato Badiraguato Culiacan 1018 107 32 15 25 20 00 1959-1999 252900 0.610974094

10. Tamazula Tamazula Culiacan 2241 106 58 30 24 56 00 1962-1999 648172 0.347839789

11. Santa Cruz San Lorenzo San Lorenzo 8919 106 57 10 24 29 05 1943-1999 1819161 0.386969472

12. Ixpalino Piaxtla Piaxtla 6166 106 35 45 23 57 20 1952-1999 1627005 0.359472719

13. Siquerios Presidio Presidio 5614 106 15 00 23 00 30 1956-1999 1044081 0.517799854

14. Baluarte II Baluarte Baluarte 4635 105 50 30 22 59 00 1947-1999 1774999 0.42

15. Acaponeta Acaponeta Acaponeta 5092 105 20 30 22 29 00 1945-1999 1362309 0.38

* Denotes basins w hich drains to the east of the SMO

The streamflow regime in NW Mexico is dominated by a strong summertime signal concomitant with summer monsoon rains (Fig. 2a). All basins show a distinct summer maximum in monthly flow volume. Interannual monthly streamflow variability (quantified as the coefficient of variation of monthly flow volume, Fig. 2b) is lowest during the summer months indicating that the higher flows are a persistent feature. There is marked flow variability in the low flow season in the spring and also in the fall. The increased variability in the late fall and early winter are likely due to land-falling tropical storms. In most basins, the months with maximum flow volume are summer months. This is not universally true though as some basins show fall and wintertime maximums.

Figure 1

Fig. 2a

Fig. 2b

Fig. 2c However, the clear signal in the annual cycle of streamflow does not necessarily imply increased predictability in summertime streamflows. Figure 3 shows the 1 month lag autocorrelation values for the 15 test basins. While low flow months tend to have a strong serial correlation the transitional months of May and Jun and the summer months of June, July, August, and Sept. each possess comparatively low correlation values with the respective preceding month’s streamflow.

Fig. 3

Figure 4It has been suggested that runoff in the NAM region is controlled more by precipitation characteristics (intensity, duration and frequency) than by seasonal precipitation totals (Gochis et al. 2003a). We examine this first by looking at precipitation features obtained from a new event based raingage network recently established in NW Mexico. (Gochis et al. 2003b)

5b

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 2 4 6 8 10 12 14 16 18 20 22 24

Time of Day (LST- Local Solar Time)

Pre

cipi

tatio

n R

ate

(mm

/hr)

Network Mean (n=47)

0-500 (n=14)

500-1000 (n=10)

1000-1500 (n=1)

1500-2000 (n=9)

2000-2500 (n=11)

2500-3000 (n=2)

Figure 5

Using data from 2002, there is evidence that supports a maximum in precipitation occurrence along the western slope of the SMO. While precipitation is less frequent at lower elevations (0-500 m) events here tend to possess higher intensities.

Table 2

The diurnal cycle of wet day rain rates (Fig. 5) also show a general relationship with elevation. Precipitation usually begins earliest at the highest elevations and progressively later at lower elevations. The lowest elevation band (0-500m) also shows evidence of nocturnal activity. Disregarding the 1000-1500 m band, the 0-500m band has the highest wet-day hourly rain rates. (Note: The strong maximum in the 1000-1500m el. Band is currently felt to be an artifact of poor sampling in this region.)

Table 3

To obtain an understanding of the rainfall runoff relationship in the NAM region we calculate the runoff coefficient (=discharge/precipitation) for the 15 test basins. Lacking a long time series of the event data presented above we used the 1 degree CPC gridded daily precipitation product (Higgins et al. 1996). This product is gridded from available historical gage precipitation measurements from the climate observing network across Mexico. Basin average precipitation values were calculated for each basin and used in calculation of the runoff coefficient. We used JAS (July-August-September) values of both precipitation and streamflow. Various combinations of months and 1 month lag periods were also calculated but the results changed little. As can be seen from Table 3, mean values of the seasonal runoff coefficient varied from 9-43%. Smaller values of the runoff coefficient (between 9 and 20%) appear to be confined to the northernmost basins. Standard deviations, however, were often in excess of 50% of the mean values indicating a large uncertainty in the mean values. This could indicate a large interannual variability in runoff coefficient values, but, in this case, more likely stems from problems in the precipitation data used. The two red values in the range column indicate that runoff coefficients for some periods exceeded 1.0 which is unlikely in this semi-arid region where groundwater inputs are not suspected to be significant.

A principal components analysis was performed on both the JAS streamflow volumes and basin averaged precipitation. Loading factors were then spatially interpolated to reveal regions of coherent variability. Both streamflow and precipitation exhibit a N-S dipole structure in the first two components. This feature has been found by Brito-Castillo et al. (2002) in their analysis of reservoir inflow volumes in the same region. These features suggest there are two distinct modes which influence the precipitation and runoff regime in the NAM region. The third principal component of streamflow variability also suggests that basins on the east-side of the SMO differ from the basins on the west. (The third component of precip. was not discernable from higher components and therefore not deemed significant.

The similar patterns revealed fromthe PC analysis above suggest thatthere may be a correlation between JAS precipitation (P) and streamflow (Q). Pearson correlation coefficients for all 15 basins are given in Table 4. Statistically significant correlations are present in 9 out of 15 basins. It is noticed that all of the southern basins and those that drain to the east are significantly correlated while only 2 basins from the northwestern part of the domain are. Also shown in Table 4 are correlation coefficients between the annual southern oscillation index (SOI) and JAS precipitation and streamflow. It is evident from these values that only basins in the south are significantly correlated with the SOI. It is, therefore suggested that principal component 2 revealed above is more strongly related to tropical forcing than are basins further north.

JAS JAS JASBasin Area N -pairs P-Q P-Correl SOI-Pcp P-Correl SOI-Q P-Correl

San Pedro del Conchos 9405 41 0.63 0.12 0.22Chinipas 5098 29 0.29 0.05 -0.17Mayo 7510 36 0.20 0.08 0.25Urique 4000 27 0.25 0.08 0.02Batopilas 2033 16 0.47 0.10 0.49Choix 1403 39 0.41 0.02 0.06Sextin 4911 21 0.80 0.15 0.17Humaya 6149 29 0.49 0.14 0.10Badiraguato 1018 40 0.15 0.06 0.34Tamazula 2241 34 0.12 0.06 0.39San Lorenzo 8919 46 0.46 0.20 0.25Piaxtla 6166 44 0.38 0.32 0.40Presidio 5614 40 0.55 0.33 0.44Baluarte 4635 48 0.44 0.35 0.42Acaponeta 5092 49 0.44 0.34 0.33

Boldface indicates correlation significant at 95% level.

Figure 6

Table 4