Estimating rainfall and biomass for the pastureland zone of the West African Sahel

Acta Astronautwa Vol 19, No

1, pp 57-61, 1989 Pnnted m Great Britain All rights reserved

0094-5765/89 $3 0 0 + 0 00 C o p y n g h t © 1989 Pergamon Press pie

ESTIMATING RAINFALL A N D BIOMASS FOR THE PASTURELAND ZONE OF THE WEST AFRICAN SAHELI" J B STEWART Institute of Hydrology, Crowmarsh Gtfford, Walhngford, Oxon OXl0 8BB, England E C BARRETT Remote Sensing Unit, Department of Geography, Umverslty of Bristol, Bristol BS8 1SS, England J R MILFORD Department of Meteorology, University of Reading, Reading RG6 2AU, England J C TAYLOR Sllsoe College, Sflsoe, Bedford MK45 4DT, England and B K WYATT Institute of Terrestrml Ecology, Penrhos Road, Bangor, Gwynedd LL57 2LQ, Wales (Recewed 18 December 1987, recewedfor pubhcanon 30 June 1988) Abstract--To prowde an early mdlcaUon of below average rainfall and pastureland biomass producUon, which could lead to famine conditions, methods of estimating rainfall and blomass of the Sahehan region of West Africa using satellite observaUons were developed l0 and 30 day rainfall were successfully esUmated from the duration of rain bearing clouds, derived from Meteosat infrared radmUon measurements Blomass was estimated from the Perpendmular VegetaUon Index derived from Landsat MSS data and ground based blomass measurements for an area in the centre of the Republic of Nager The accuracy of these esUmates was found to be generally reasonable when checked against an independent set of blomass measurements These methods are to be incorporated into an operational system for tMs region of Africa

I INTRODUCTION

However, the use of satelhte data, whmh proxade frequent observations over a wade area, gives the promase of a solutaon to these problems The present paper presents the results of studies of methods for estamatmg raanfall and pastureland production from satelhte observataons Thas was the first part of an E E C funded project to develop an operataonal system for the Sahehan zone of West Africa

Sahel regions experaence great vanablhty in rainfall from year to year Agriculture and pastureland producUon of these marginal lands ~s crmcally dependent on the input of suffioent rainfall The extensave and prolonged droughts whmh occurred m the Sahel zone of N o r t h Africa during the last two decades, resulted m wade scale loss of crops and hvestock and caused masswe loss of life from famine and a major refugee problem To prevent or at least mmgate these problems ~t ~s necessary to adentffy areas of msuffioent rainfall and reduced biological producUon F o r the Sahel regions, obtaining the relevant data is parUcularly difficult for two reasons Farstly, rainfall is spatmlly extremely variable, so measurements from a low d e n m y of gauges may gwe inaccurate areal averages secondly commumcatlons between the small scattered centres of populaUon are p o o r To overcome these problems would require much greater resources than are avadable to the Sahelmn countries

2 METHODOLOGY

Instrumentation on satellites can only measure the radiation emitted or reflected from the Earth's surface or from the atmosphere and clouds above the Earth's surface It cannot measure rainfall &rectly However, the presence of clouds of ram beanng types detected by a satelhte may be used to indicate the occurrence of rainfall and lead to estimates of the associated rainfall amounts In the Sahel regzons of West Africa, rainfall comes predominantly from squall hnes of thunderstorms These thunderstorms can be adenUfied from the satelhte observations of the cloudy areas and measurements of the cloud top

tPaper IAF-87-166 presented at the 38th Congress of the Internatwnal Astronautwal Federanon, Brighton, U K , 10-17 October 1987 57 AA 19/I--E

J B STEWARTet al

58

temperatures Cloud systems which are producing slgmficant rainfall extend to high altitudes and therefore reach very low temperatures, e g below - 50°C The relationships between the hfeUme of clouds whose tops are below a range of threshold temperatures, and rainfall amounts have been cahbrated statistically against raingauge measurements There is a major problem of venficatmn which is common to any project using satelhte data to esUmate rainfall The satelhte data give estimates of the average rainfall over an area (m this project 5 x 5 km), while ground based measurements of rainfall are point values This problem is partmularly severe in semi-and areas, such as the Sahel, where the rainfall is known to be extremely variable both spatmlly and temporally Although rainfall is often the most important of the enwronmental variables which determine binlogical product]vlty m semi-and rangelands, other factors are also significant Measurement of rainfall alone is an inadequate grade for optimal rangeland management strategies Meaningful models of primary productivity must take into account the enUre range of enwronmental variables, such as soil type and differences m hydrology Part of this study was therefore concerned with the use of remotely-sensed data to map the d]stnbut]on and quantity of rangeland vegetation m order to develop such models of primary production Herbaceous bmmass was determined m a range of and grasslands wRhm a hmlted area Two radices of green vegetative cover derived from digital mult]spectral data, the Normahzed Difference Vegetation Index (NDVI) and the Perpendicular Vegetation Index (PVI) were evaluated Correlatmn curves, relating blomass with NDVI and PVI were constructed These correlations were tested using blomass values measured independently

20"W

10"

0

10"

20*

30"E

30'

30*

2O*

2O"

10"

10"

0

0

IO'W

0

10"

20*E

FIg 1 Map of West Africa showing the extent of the Meteosat data The shaded square shows the approximate area in the Republic of Niger where the ground surveys were carried out and for which Landsat MSS imagery was available

3 EXPERIMENTAL AREA

The methods described here are intended for apphcatmn throughout the Sahehan zone of Africa However, their development was dependent upon large volumes of rehable data from conventional sources For practical reasons, a more localized area was therefore chosen for the experimental phase of the project, described in this paper This work was carried out in the Repubhc of Niger, where members of the Project Team have been collecting experimental data for a number of years and have built up good relations with national agricultural and meteorologmal msUtutlons Figure l is a map of North Africa showing the part of the Meteosat Imagery wMch was available for this project, l e from 14°E to 7°W and 9°N to 25°N 4

RESULTS

4 1 Spatial varlabdtty oj rainfall The rainfall from Individual storms vanes rapidly with distance due to the spacing and fluctuations of the active cells w~thln the storms (see Fig 2) Consequently, for individual rain events, a single ram gauge may g~ve a rather poor representatmn of rainfall experienced over areas corresponding to the resolutmn of satelhte sensors To measure the spatial vanablhty of rainfall, an experiment was set up near Ibecetene (15°12'N, 5°48'E) m the Repubhc of Niger m an area with a mean annual rainfall of 350mm A network of 36 rain gauges was installed over an area of 10 x 10 km at a spacing of 2 km The total rainfall received during July and August 1985 vaned over the 10 km gnd by a factor of over two The lowest value was 128 mm, the highest was 273 mm and the mean was 215 mm Expressed another way, these results show that the measurement of rainfall by a single gauge w]thln this area could indicate a period of very poor ram (as low as 60% of the average) or a period of plentiful rain (as high as 127% of the average) depending on the locatmn of the gauge

4 2 Estimation of average 10 and 30 day rainfall Two different methods were developed for the automatic est~mauon of average rainfall over 10-day and monthly periods Both methods took the presence of cloud at h]gh altitudes (md]cated by low temperatures observed m thermal infra-red data from Meteosat imagery) as indicative of the probable Incidence of rainfall The first method used chmatologlcal data to denve esumates of rainfall from satelhte observatmns of high-level cloud Maps of the number of ram-days m a given penod were produced by cumulating daffy records of the dlstnbutmn of h]gh-alUtude cloud observed by satellite A first approxlmatmn to the estimate of total rainfall was made by multlplymg the accumulated

Rainfall and bmmass of Sahel

g

59

10

Table 2 The relationship between the duratmn of cold cloud tops (-60°C) and rainfall at 109 stations ,n Niger dunng July 1985 n is number of cases Rainfall Cloud Lower Upper duration Me&an q u a r t i l e quartile (h) n (ram) (ram) (ram)

05

0 0 5-45 5 0-9 5 100-195 20 0-29 5 >30

U

0

i

~

|)

S0

100

150

Distance Apart (km)

2 Correlation of rainfall amounts from large-scale convective storms from sRes around Nlamey, N~ger

Flg

numbers of ram-days by mean rainfall per rain-day denved from climatological atlases This was done on a plxel by pixel basis The estimated values for total rainfall at sRes of synoptic meteorological statmns were compared wRh observed values, and a weighting factor was computed to correct esttmated to measured values This adjustment was then apphed across the whole area to produce the final estamates of mean ramfall These esUmates are compared with observed ramfall reports from major statmns m the Western Sahel m Table 1 The second method related rainfall to the total cold cloud duratmn derived from 19 Meteosat images per day over periods of 10 and 30 days from June to August 1985 In this case, ramfall data for cahbratlon purposes were obtamed from synoptic meteorological data from 12 statmns and records from up to 120 supplementary ram gauge statmns The study suggested that m this partacular region a temperature threshold of - 6 0 ° C generally dtsenmmated between non-preclpRatmg clouds and those which produced ram at some Ume dunng their lifetime Good correlatmn was demonstrated between cold cloud duratmn and medmn ramfall (Table 2) Part of the scatter m the quantRat~ve esUmates as due to the extreme vanabflRy in the spatial distnbutmn of ramfall m this regmn, as descnbed earher m thts section

R2 value

coefliocnt

(%)

1-10 July I 1-20 July 21-31 July

0 61 0 66 0 57

36 7 43 5 32 2

1-10 Aug I 1-20 Aug 21-31 Aug

0 64 0 50 0 66

40 8 24 5 44 0

Penod

1 5 12 53 64 83

14 27 65 115 117 ll9

4 3 Vegetation mapp,mg and esnmatzon o f bwmass To facilitate integration of the results, th~s part of the work was also carried out near Ibecetene m an area 25 x 25 km, using Imagery and field data from the period October 1984 to September 1985 Supervised class~ficatmn of the ~magery was performed using a maxtmum hkehhood algorithm The resultant classified tmages were used to stratify the test area m order to select experimental rues that were representative of all the mare cover types experienced there It was found that the main factors deternunmg spectral response m all cover classes were the soil type and the extent of herbaceous vegetation cover Two vegetaUon Indices, the NDVI and the PVI were mvesUgated as possible means of estimating b~omass from remotely sensed data Basic sod/vegetation spectral relationships were examined

100

a so

CorrelatJon

7 16 40 85 90 101

Maps of cold cloud duration were prepared for each 10-day period and monthly for June, July and August 1985 for the whole of the Repubhc of Niger south of 19°N In these maps, the 8-h duration contour was shown to correspond to about 40 mm ram and the 16-h duratton contour to about 80 mm but some d~fference between months was noted The 10-day maps are useful for agro-meteorologlcal purposes, even w~thout cahbratlon, since they clearly ~dentlfy areas without convective storms, where annual vegetatmn would be severely stressed

A

Table I Summary of regresston statmtlcs for observed rainfall reports from major stattons m the Western Sahel and the eqmvalentsatelhtedenvcd rainfall estimates

4 4 4 43 43 II

i

200

(a)

.•Sand

(b)

~

d

i,°° /

Leterlfe

" Laterlte M ) $0 R Reflectance (~)

0 100

R Reflectance (OV)

FIg 3 Sotl 1,nes derived from (a) field radiometer--red waveband, R (0 62-0 68 #m) and near infra-red waveband, IR (0 72-0 98 #m) (b) Landsat MSS---red waveband, R (060-070#m) and near infra-red waveband, IR (0 70-1 1 gin)

60

J B STEWARTet al

Table 3 Companson of mean values of NDVI and PVI for cover classes identified w t h m the Ibecetene study area Cover class

Ref No

NDVI

I 2 3 4 5 6 7 8 9 10

0 049 0 072 0 073 0 102 0 260 0 098 0 112 0 095 0 099 0 228

Latente Clay Latente Clay outwash Sand Dense bush Bush on Latente sand Medium bush Thin bush Very thin bush Water

PVI (digital value) 02 04 - 17 07 21 9 24 42 11 15 16 3

using field ra&ometnc data and Landsat MSS ~magery and the vahdity of the PVI approach was demonstrated (Fig 3) Results from field vegetat]on surveys were used to cahbrate and test vegetat]on m&ces derived from satelhte ]magery The PVI was found to be more sensmve than the NDVI m condmons of low blomass ( < 100 kg ha-]) (Table 3) F]gure 4 shows the values of PVI plotted against the measurements of blomass The empmcal relat]onshlp fitted to the data ]s also shown, ~ts equation ~s B=65

p2,

n=8,

r2=099

where B Is blomass and P is the PVI expressed m &gltal numbers The PVI was found to be well-correlated with measured herbaceous blomass An independent set of measurements of blomass provided by the International Lwestock Commission for Africa (ILCA) was used to check satelhte estimates of blomass, with encouraging results (Table 4) 5 CONCLUDING REMARKS

The study of the spattal variability of rainfall showed that even when the rainfall was summed over 1500

l (ks/ha) Biomass

1000

500

(ii) ( (I) 4----

-5

5

10 15

Perpendicular Vegetation Index

rig 4 Calibration curve for estimation of dry grass btomass from the PV1 (l) l SE either side of the mean PVI for soft (n) Observed range of PVI values for bare soil plxels

Table 4 Errors In predicted levels of dry herbaceous biomass at ILCA test sRes compared with biomass measured between 26 August and 3 September Blomass (kg ha 1)

%Error

ILCA Site No

Measured

PVI

NDVI*

PVI

NDVI*

2 3t 5 6 7 17 18

55 744 2 342 5 125 488 4 8775 4599

66 521 2 60 122 510 8 9400 2190

63 562 2 9 I 194 278 4 8627 2452

200 30 0 98 2 24 46 71 524

145 24 5 97 3 552 43 0 17 467

*Second order regression, 6 points only "?Partial cloud cover

2 of the 3 main months of the wet season, ramfall measured in two standard raingauges only 10km apart could differ by as much as a factor of 2 If the only measurement of ramfall had been by the gauge that received the small amount, then the wet season would have been considered very poor, whereas the gauge with a large amount of ramfail would have suggested a year of plenty To have gauges as close as 10 km would require 12,000 gauges to cover the whole of the Republic of Niger which is clearly not possible As an alternatwe, the results of these investigations into estimating monthly rainfall using satelhte data look very encouraging On the basis of the relaUon between rainfall and the duration of clouds whose tops reach a height where the a]r is below - 6 0 ° C , an operational rainfall estimation system IS being developed With the improvements m hardware and software tt ~s now possible to construct such an operational system based on a personal computer such as an IBM PC The planned operational system would give estimates of rainfall for the various hydrolog]cal reg]ons of the Sudan So this wdl be an example of reformation based on satellite data, which would be of &reet use to the end user, in th~s case the Sudan Meteorological Service Mult~spectral satelhte imagery has been successfully cahbrated against ground measurements of blomass Tests against independent measurements of b~omass confirmed the vah&ty of the estimates denved from remotely-sensed vegetation m&ces An operational pastureland momtonng system must be sensltwe to frequent changes m vegetation status The frequency of Landsat overpasses is lnsufficmnt for th~s purpose Meteorological satelhtes, such as the NOAA polar-orbiters or Meteosat, collect data at a statable frequency However, low-resolution meteorological satelhte data present severe dffficulues m relating ground-based measurements to satelhte data, averaged over areas of 1 to 100 km 2 It has been shown how this problem might be overcome by using a small number of higherresolution Landsat ~mages to estabhsh the basic cahbrat~on between vegetation index and b~omass and then applying these cahbrat]on data over larger

Rainfall and blomass of Sahel areas and at higher frequencies, using imagery from meteorological satelhtes

Acknowledgements--The authors wish to acknowledge the efforts of the other team members D G Hewett of ITE, C H Power of Bristol Umverslty, G Dugdale of Reading

61

Umverslty, A S Belward and M A Kee~h of Sdsoe College and the actwe support of the Centre Agrhymet m Nlamey and the National Meteorological Service of the Repubhc of Niger The work was partially funded by the Commission of the European Communmes Development Directorate and by the Umted Kingdom Overseas Development Admlmstrat~on