A large part of rain in the northern tropics is drained off by rivers running through the Sahel (Fig. 1). These rivers feed the large floodplains and other wetlands in the semi-arid Sahel. The annual discharge of the rivers varies considerably. This is not caused by variations in rainfall in the Sahel proper (being too low to have an impact on the river flow), but is closely correlated with the rainfall further south in the catchment area of the rivers. The Senegal, Niger, Chari, Logone and Nile lose a lot of water during their passage across the Sahel, due to evaporation and infiltration. Especially in dry Sahel years, the rivers lose a large part of their flow. After a series of dry years the ground water table recedes and the rivers consequently lose even more water. River flows in the Sahel therefore not only depend on rainfall in the preceding months, but, to a large extent, also to rainfall in earlier years.
Most Sahel rivers had a natural flow until about 1980, but this state has changed considerably since then. Due to the construction of the Manantali dam in the Upper Senegal River, a huge reservoir of 11 km3 came into being. During the rainy period a large part of the river flow is stored in the lake to be gradually released in the dry months. In this way electricity can be produced and irrigation of farmland is possible during the dry period. The Selingue dam has a similar impact on the Upper Niger River as the Manantali in Senegal and Mauritania, although less drastic due to its smaller size. In North Nigeria and Cameroon dams have also affected the river flow, with significant consequences downstream for the seasonal floodplains and marshes.
Fig. 1. The three major drainage basins in West Africa: Senegal, Niger and Lake Chad, and (shown in purple) the 12 largest water reservoirs. Manantali and Selingue are the only two big reservoirs in the Upper Senegal and Upper Niger, respectively. From: Zwarts et al. 2009. Living on the edge.
The Niger River is 4184 km long and its drainage basin covers an estimated 2.2 million km2. Like other rivers in West Africa, the Niger demonstrates huge between-season variations in discharge. For instance, the average discharge of the Niger at Koulikoro (SW Mali) in September is thirty times larger than in April. This is caused by the short but intense rainy season, reaching a peak in August. It takes some time before all this surface water finds its way via shallow gradients into the Upper Niger, which normally reaches its maximum height in September or October before it reaches the Inner Niger Delta. Sahel rivers, draining lowland catchments, have a characteristically low flow rate. The length of the Niger means that it takes 6 months before the rainfall in Guinea reaches the ocean.
The Niger and its Niandan, Milo and Sankarani tributaries rise in the Guinean Highlands (Fig. 2). The most northerly branch, the Tinkisso, originates in the Fouta-Djalon. The main tributary to the Niger is the Bani, which drains southernmost Mali and the northeastern corner of Ivory Coast. After the Bani flows into the Niger near Mopti, at the southern edge of the Inner Niger Delta, there is no further run-offf from eastern Mali and Niger. Consequently, evaporation gradually diminishes the river flow.
The total catchment area of the Bani (129 000 km2) is nearly as large as the rest of the Upper Niger Basin (147 000 km2). Yet the discharge of the Bani is less than half of the Niger, because the Bani sub-basin receives less rainfall than the other sub-basins of the Upper Niger.
The Inner Niger Delta in Mali is huge. On topographical maps from the 1960s, a total surface of 36,000 km2 is designated as floodplain (Fi.3). When the water level starts to rise in July in the southwestern part of the Delta, the plains in the northeast are still dry. By the time that the northern plains become flooded two months later, the water level is already declining in the south. The area covered by water at any one time amounts to 25,000 km2. Such a large flood extent is only possible when the combined inflow of Niger and Bani, the major tributary, exceeds 55 km3 in the rainy season. In most years, the inflow is smaller. During the disastrous drought in 1984, the inflow was only 15 km3, and the flood extent did not exceed 7800 km2.
The Inner Niger Delta not only stands out because of its size, but also due to its hydrological dynamics. Between July and December the water rises by more than 6 m in wet years, to decline by the same amount in the following months. In extremely dry years, however, the flood level rises only by 3 m.
Fig. 3. The floodplains (light blue) and permanent water bodies (dark blue) of the Inner Niger Delta, as indicated on the topographical maps of the Institut Géographique National. The maps are from 1956, and based on aerial photographs and field work in the early 1950s, a period with very high floods. From: Zwarts et al. 2009. Living on the edge.
A higher flood also means a larger area being inundated. The relationship between flood level and flood extent is known; see atlas. The flood viewer allows you to see the predicted flood extent. The flood extent is given for a range, taking into account the confidence interval of the predicted peak flood level: minimum = “certainly flooded”, maximum = “possibly flooded” and mean = "most likely flood extent" halfway between minimum and maximum.
The peak flood level may be predicted some months in advance. Using the same methodology, it is also possible to predict the curve during the deflooding, and thus also to predict when floodplains will become accessible for grazing cattle during receding water. The prediction given here refers to when the water level at the gauge of Akka has declined to 200 or 100 cm; see deflooding. At that water level the majority of the floodplains are exposed. A selection has been made for the water level of 200 and 100 cm in Akka, but the prediction for the deflooding may easily be done for other hydrometric stations and different water levels.
OPIDIN is meant as early warning system for the habitants of the Inner Niger Delta and all people making their living there. An extremely high flood may cause problems at a local level (e.g. flooding of houses), but the consequences of an extremely low flood are much more serious. The low floods in the 1980s were a disaster with a very low production of rice and fish.
The potential users of OPIDIN may be assembled in 13 categories. Forecasting the flood level in August may help, for instance, fishermen and herders to plan their activities, but for rice farmers this information comes one month too late. Moreover, for planting rice the expected rainfall is more relevant. Global forecasting of rainfall are available; see meteo. The recent rainfall in the Upper Niger Basin will be included in the evaluation of the flood forecasting such as given in the weekly bulletin.
|1. Habitants of the floodplains. People in the Inner Niger observe the daily rise of the water level between July and October, but they cannot forecast till how long the water will rise and when the peak is reached. OPIDIN gives this essential information. All old settlements in the Inner Niger Delta are on high grounds so they are not flooded even at the highest floods. Since 1969 the floods have been 1-2 m lower than these extremely high floods, and some people have settled on lower grounds. These high floods seem to have disappeared from the collective memory. OPIDIN gives “an early warning” to those people having built houses on grounds being prone to flooding.|
|2. Rice farmers on the floodplains (“submersion libre”). Farmers in the southern Inner Niger Delta grow a rice variety (riz flottant or floating rice) which is well adapted to grow upwards with the rising water during the flooding. They sow the rice grains before the first rainfall in the hope that the rains come before the flood and makes the rice sprout before the flood arrives. After a flooding period period of about 3 months the rice can be harvested. Farmers in the Inner Niger Delta have to decide where they should plant their rice. During the Great Drought (1968-1993) many farmers decided to give up their traditional rice area and start to reclaim new ricefields lower down in the inundation zone. OPIDIN cannot help the farmers to decide where to sow their rice, but can forecast the flood level and thus, indirectly, their yield.|
|3. ORM et ORS (“submersion semi-controlee”). Opération Riz Mopti (ORM) and Opération Riz Segou (ORS) manage large areas near Mopti and east of Segou, along the Niger River. There is no active irrigation. There are dikes and sluices to delay the flooding, if necessary, and manage the water level during the deflooding. Hence it is a polder (casier in French), but the water management is passive: if the flood does not rise enough, the area remains dry. Thus, as for the farmers on the floodplains, OPIDIN is of limited use.|
|4. Rice farmers in irrigated areas (“submersion controlee”). OPIDIN is hardly of interest for people growing rice in irrigated areas within the Inner Niger Delta (for instance in small irrigated perimeters) if the irrigated fields are on high grounds and the water is pumped from the Niger River nearby. However, irrigated rice fields have also been constructed in recent years on the floodplains itself. In the latter case dikes around the irrigated fields have two functions: (1) keep the water within the fields (for which a low dike is sufficient), (2) keep the water out when the floods are high (for which a high dike is needed, certainly if the site is situated low on the floodplains). OPIDIN may warn the people in time if a high flood is expected (so they can take precautionary measures to defend their dike).|
|5. Farmers on the emerging grounds during the deflooding (“zone de décrue”). People grow crops and vegetables on the emerging, still wet grounds. The time of deflooding is highly variable and differs several months between years, especially in the northern part of the Inner Niger Delta. OPIDIN could predict already in August when an area will be deflooded between January and May.|
|6. As 5, but in shallow lakes and depressions (“bas fonds”). People also grow crops and vegetables on the emerging grounds in shallow depressions and larger lakes. OPIDIN will be of a limited value for these farmers, since the water level in these water bodies will usually be not connected to the river system, by which the decline of the water level is not determined by the declining water level in the river system, but by the evaporation in the isolated water bodies. However, OPIDIN is in another way relevant for farmers in these lakes, since it may forecast whether the flood will be high enough to fill the lake.|
|7. Water managers (e.g. large lakes in northern Delta). The water level in Lac Horo is artificial since a sluice has been constructed in the creek connection between the Lake and the Niger River near Tonka. The way the area is exploited by fishermen and farmers varies during the course of the season and depends on the water level. The water manager has to take into account the different, partly contradicting interests. OPIDIN may facilitate the decision process since the expected flood curve at Niafunké near Tonka may already be predicted months before. The same applies for Goundam (Lac Faquibine).|
|8. Livestock. Millions of cows, sheep and goats migrate into the Inner Niger Delta during receding water where they feed on dried-up floodplains. The majority of the floodplains of the Inner Niger Delta is covered by four floating aquatic grass species: wild rice, floating rice planted for consumption and two plant species locally known as didere and bourgou. As water levels decline, these plants, especially bourgou, offer a good food resource for the livestock during the long dry season. OPDIN indicates when the floodplains will become available for the livestock, but also what they can expect about the food supply (directly linked to the flooding: a higher flood results in a higher bourgou production).|
|9. Fishery. Most fish is captured in the Inner Niger Delta during the deflooding when the plains are drained and all fish get concentrated in the creeks and last remaining, isolated water bodies. The fish campaign is usually at a maximum in January-March. In the present situation fishermen invest in new nets or a new boat as soon as it is obvious that the flood will be high and thus also their captures. OPIDIN allows them to make these decisions one or two months earlier.|
|10. Transport. The Niger river plays an important role in the transport of goods and people. Particularly during the wet season, boats are the most popular means of transport in the Delta. Not only does the river transport allow people to reach remote places, transport by boat is relatively inexpensive compared to road transport. OPIDIN can be used as a tool to indicate the length of the navigation periods for boats of different size.|
|11. Local authorities. the Governor of Mopti has to decide in October when the cows are allowed to enter the Inner Niger Delta. OPIDIN can assist to fix the dates at which the water level has fallen enough to allow grazing, without causing problems for the rice farmers.|
|12. National and international aid agencies. Floodplains are extremely productive biological systems and nearly everywhere in the world attract for this reason many people. That is also true for the Inner Niger Delta. The Inner Niger Delta is a fully flood-dependent economy, being very productive in years with a high flood, but with very low yields in poor years. At present, weather satellites register clouds all over the world and produce estimates about the daily rainfall. This information has been entered in early warning systems (GIEWS, FEWS). So, the food aid agencies are informed about areas where crop failures are to be expected. The flooding of the Inner Niger Delta, and thus the yield of natural resources in the delta, is not linked to the local rainfall. Hence, OPIDIN provides an important additional tool as early warning system to (inter)national aid agencies.|
|13. Contribution to national policies and strategies. OPIDIN can contribute directly to some key aspects of national policies and strategies related to water and land management, directly to IWRM implementation in the delta and in the Niger upper basin and to conflict prevention; it can support appropriate decisions for a good balance between economic development and a sustainable environment; it can help the populations to improve food security through a better knowledge of hydraulic conditions; it can help regional authorities to take decisions about water and land sharing between competitive users ("calendriers de traversée"); it can help the Government and the international community to anticipate possible water crisis and food shortage and to plan earlier and adequate responses; and it can help everybody to take in account the effects of the global climate change and its impacts on the water availability in the Niger basin.|
In the Inner Niger Delta, flood height may reach six metres, slowly engulfing an area of 400 by 100 km. Fortuitously, the seasonal rise and retreat of the flood in this area has been measured daily by the DNH at several hydrological stations (Fig. 4) over many decades, producing a time series of great value. The water level is low from April to June, and begins to rise in July. In years of low river flow, the water reaches a height of about 3.5 m, peaking in late October. At high river flows, although the water level rises at the same daily rate, it does so over a longer period, peaking at 6 m by late December. Usually, lower-level floods cover floodplains for four months only (October-February), but high floods inundate them for twice as long (September-April). During the flooding (crue) and the deflooding (decrue) the water level rises and declines 3-5 cm per day. This gives the opportunity to predict the flood level in a week or in a fortnight.
The water level in Mopti is in the dry period, on average, 100 cm on the local scale. In dry years, the flood level rises 380 cm above this level, but in wet years more than 600 cm (Fig. 5). The water level in June, and even in July, cannot be used to foretell the peak flood level. However, when the water level in August is still low, one can be rather sure that also the maximum flood level will be low too, while a high floods may be foreseen if the water level in August is high. When the water level in Mopti on 1 August is 200 cm, it is possible to predict that the maximal flood level will be reached already in October a peak level of about 500 cm, while it is at the same date already 400 cm, we may predict that the peak flood level will be reached in November and be about 700 cm. The scattering around the regression line is rather wide, so the predicted level is not yet precise. Ten days later, the prediction is already better and on 30 August, we may indicate rather accurate the peak flood level and also when it will be reached. As an example, Figs. 6 and 7 show the relationship between the level of the peak flood and the water level reached on 20 August. During the course of September, the predictions for the flood level become more precise, but the date at which the peak is reached remains difficult to predict. All details regarding the methods are given in a report.
To know the predicted flood level, go to flood viewer.
OPIDIN is a set of curvilinear regression equations based on the daily measurements of the water level in eight hydrometric stations in the Inner Niger Delta: Ke-Macina, Mopti, Akka, Niafunke, Dire, Douna, Beneny Kegny and Sofara (Fig. 4). For all these station long series of measurements are available: Mopti and Douna since 1922, Dire since 1931 and Akka since 1955. The most important station for us is Mopti since it measures the water level after the Bani has joined the Niger River. Also Akka is important due to its central position in the Inner Niger Delta.
Fig. 4. The eight hydrometric stations along the Lower Bani and in the Inner Niger Delta used in OPIDIN.
We calculated the relationship between the peak flood level in Mopti, in Akka and in Dire as a function of the water in Mopti on 1 August, 5 August, 10 August, etc. until 10 October. The predicted values for the days between were interpolated. The same calculations were done for the peak flood level, but also for the date at which the peak flood is reached. The 95% confidence interval was calculated. The result is a very large table from which the predicted peak flood (level and date ± 95% confidence interval) in Mopti, Akka and Dire is given as function of the large range of water levels for every day between 1 August and 15 October.
Sélingué reservoir has changed the seasonal variation in the flow of the Niger. During the (early) rainy season, a part of the water is stored to fill the reservoir, which is emptied during the dry season. The Sélingué reservoir is used since 1982. To take its impact into account, the reservoir was entered as a dummy variable in the multiple regression equations; more details are given a . The outcome of these calculations is given in the .
Fig. 5. The variation in water level (cm) in Mopti since 1923 between 1 June and 1 June the next year. When the flood is low, the peak is reached in early October, but in wet years, the peak is more than a month later.
OPIDIN uses this data set to predict the peak flood in relation to the water level measured 2-3 months before.
Fig. 6. This graph shows the year-to-year variation in the peak flood level in Mopti since 1943 (red line) and for the same period the water level on 20th August (blue line). If the water level in Mopti on 20th August is 300 cm, the peak is 200 cm higher, but if the water level on 20-8 is 550 cm, the difference is less, 150 cm.
Fig. 7. The same data shown in the graph above, but now plotted against each other. The linear regression line is shown. The 95% confidence interval amounts to 65 cm. Later in the season, the interval gradually declines to 12 cm.
As described in the previous section, OPIDIN is based on the measurements of the water level in Mopti in August-October. Since the water level in Mopti is determined by the rainfall in the Niger Basin upstream of Mopti during the preceding weeks, an alternative might be to base the prediction of the flood on the cumulative rainfall in the preceding weeks. If possible, the big advantage would be that the flood prediction can be advanced a fortnight, or possibly even more. The daily rainfall is given on the FEWS website. This site gives for entire Africa the estimated actual daily rainfall, but also the rainfall for the last six days and the forecasted rainfall for the coming six days. We downloaded the 4896 daily rainfall maps since 1 January 2001 in a GIS system and calculated the total daily average rainfall for eight sections of the Upper Niger Basin, two from Guinea, split up for the Niger (N1) and the Bani (B1) and six from Mali (Bani: B2 and B3 and Niger: N2 and N3, Delta: D2 and D3); see Fig. 8. The data were used to calculate per year the cumulative rainfall in these eight sections during the course of July, August and September and relate this to the peak flood later in the year. To make a long story short, we were not able to improve the flood prediction when we used these meteorological data instead of the hydrometric measurements in Mopti.
Fig. 8.Map showing the eight sections within the Upper Niger Basin (border indicated in red) for which we calculated the daily rainfall such as given on the FEWS-site. The maps show, as example, the rainfall on 20-8-2013, with yellow = <5 mm rain, blue = 40-60 mm and red = 180-250 mm. .
The best option appeared to be to combine the hydrometric and meteorological measurements. We investigated several ways to combine both data set and finally made the choice to run the original hydrometric regression equations in OPIDIN to predict the peak level and the timing of the flood and thereafter to calculate for all years since 2001 the difference between the predicted and actual flood and regressed this error against the rainfall in the Upper Niger Basin during the preceding weeks. This approach is statistically simple, but it is also logical. The water level measured in Mopti in August or September depends on the rainfall upstream since June, but is fully independent of the most recent rainfall in the Upper Basin since it will take time before the rainfall some 100 kms from Mopti has an impact on the rising water level in the Inner Niger Delta. Hence the recent rainfall can be used in OPIDIN as a tool to improve the prediction, statistically independent of the most recent measurement of the water level.
The methodology may be illustrated with an example. In 2013, the water level in Mopti was until 11 August so low that we feared for a very low flood. Fortunately, the rainfall in the Upper Niger Basin in early August has been higher than normal for this time of the year. Hence we expected that the next fortnight the water level in the Inner Niger Delta would go up faster than the weeks before and that the peak flood level would be much higher than predicted from the water level measured in Mopti on 11 August. Indeed there was a fast increase of the water level between 11 and 21 August 2013 by which the prediction of the flood level could be upgraded in late August. In other words, due to the late start of the rainy season in 2013, the OPIDIN predictions were too low until late August, but by integrating the most recent rainfall in the model, we could correctly predict the peak flood from early August onwards, about a fortnight earlier than OPIDIN as hydrometric model.
Using hydrological models, it would be possible to estimate the time between the rainfall somewhere in the Upper Niger at a certain day and the time it takes before this water has reached Mopti. An alternative is to do statistical analyses to find out how OPIDIN can be improved the most when using the recent rainfall. First, we did so including or excluding the rainfall in the Inner Niger Delta itself and found that inclusion of the local rainfall in the northern Inner Niger Delta did not improve the prediction. After that we calculated for each day between 21 July and 16 October the predictive power of the cumulative rainfall during the preceding 1, 2, 3, …, 28 days in the entire upper Bani and Niger and southern part of the Inner Niger Delta combined. For nearly all dates the correlation was low when we added the rainfall for the preceding 1,2,3 or 4 days, but the correlations improved when the rainfall was added over a longer period up to 20-25 days, after which there was no further increase and for most dates a decline of the correlation. We decided to sum up the rainfall for a time period of 18 days for each date and to use this fixed time period for all dates between 21 July and 15 September (e.g. rainfall added for 6-23 July on 23 July, rainfall added for 7-24 July on 24 July, etc.).
The peak of the flood in the Bani River is in Douna about 20 days earlier than in Sofara (230 km downstream of Douna) and a similar retardation exists for the Niger River between Ke-Macina and Mopti. To this must be added some days between the Douna and the Upper Bani and about a week between Ke-Macina and the Upper Niger. Thus, the increase of the water level in Mopti during the raining season, depends on the rainfall in the Guinean part of the catchment area (Bani1 and Niger1 in the map given above) four weeks earlier. However, not more than half of the rain in the catchment area upstream of the Inner Niger Delta falls in Bani1 (9.2%) and Niger1 (40.2%). The retardation between rainfall and water level in Mopti will be three weeks or less for the rain falling between Mopti and the Malian part of the Upper Niger Basin. Thus, the calculated optimal average time span of 18 days appears to be a realistic compromise.
Fig. 9. The actual peak flood (cm) in Mopti plotted against the predicted peak flood on 6 August during 13 years (2001-2013). The prediction is solely based on water level in Mopti on 6 August (hydro model).
Fig.10. The difference between the actual peak flood and the predicted peak flood on 6 August (taken from the graph above) plotted against the rainfall in the Upper Niger and Upper Bani during 18 days before 6 August.
Fig. 11. The actual peak flood (cm) in Mopti plotted against the predicted peak flood on 6 August during 13 years (2001-2013). The prediction is based on the water level in Mopti on 6 August corrected for the rainfall in 18 days before 6 August ("hydro+meteo model").
Figs. 9-11 show in a nutshell how hydro-meteo-prediction in OPIDIN improves the original hydro-prediction. Fig. 9 shows for 6 August during the last 13 years the relationship between the predicted and the actual peak flood in Mopti. The scattering around the regression line is large. The deviation from the calculated linear regression line is plotted against the rainfall in the 18 days before 6 August in Fig. 10. The regression line in Fig. 10 can now be used to improve the flood prediction. The result is given in Fig. 11. Obviously, the prediction in the hydro-meteo-model (Fig. 11) is much better than the prediction of the hydro-model (Fig. 9), as can be seen from the higher correlation. This does not imply that the hydro-meteo-prediction is all years closer to the truth than the hydro-prediction. The statistical analysis shows that the average error becomes less and thus also the risk of a wrong prediction. The scattering around the regression lines in Fig. 11 is used to estimate the confidence interval of the predictions. What is shown here for 6 August, was done for all dates between 26 July and 15 September. The rainfall in the preceding weeks has a large impact on the prediction in early August, but it becomes less later in the season and the correction is very small in September.
The water level in August or September may also be used to predict the date at which the water level has declined to a certain level. We selected the date at which the water level during the deflooding has declined to 200 cm and 100 cm at the gauge of Akka, since that is the level at which nearly all floodplains are emersed. In the same way as described above for de peak flood, we calculated curvilinear regression equations relating the date of deflooding (200 or 100 cm at Akka) to water level in Mopti on 1, 10, 15 August, etc. The result is given in deflooding.