Concluding thoughts

Over the past 3 months, I have covered a range of aspects and issues related to WRA. 

We have now understood what WRA is and the rising importance of WRA in Africa, for that

1. It allows a better management: more fair, more equitable for different stakeholder, better for the environment, social justice, maintenance of cultural and socioeconomic activies
2. It allows a better understanding for both the hydroclimatology and groundwater within the hydrological system.
3. It simply saves money!

We have also understood the role of citizen science and its potential in achieving a greater quality and volume of data collection than the traditional methods in some cases as well as empowering those whose voices often go unheard in the process of water resources management.

I sincerely hope you have enjoyed reading my blog as much as I have enjoyed writing them. I also wish my blog will help to raise the much needed awareness in the importance of WRA and its relationship to the management of water resources. :)

The role of citizen science in hydrology: combating lack of data and joining science and local policy

As I mentioned last week, one of the most important aspects of citizen science is its validity and whether the data can pass the stringent scientific quality control. In this study, the researchers explored this particular aspect and gave some valuable advice on the wider application of community-based hydrological and meteorological monitoring programme.

This study is initiated by the AMGRAF (Adaptive Management of shallow Groundwater for small-scale irrigation and poverty alleviation in sub-Saharan AFrica) project where its main goal is to investigate the potential of utilising shallow groundwater resources for small-scale irrigation and poverty alleviation. This therefore links nicely with one of my goals of the blog, which is to explore how the assessment of water resources come to inform policy actions.

The location of the study is at Danila woreda, Ethiopia (figure 1) and the installed monitoring points are shown in figure 2.

Figure 1. Study area.

Figure 2. Locations of monitoring points (close to arrowhead in Figure 1). MW= monitoring well, DSC = Dangesheta Service Cooperative, DAO = Dangesheta Agricultural Office.

Why was the community involved?

There is very limited data available for rainfall, river discharge and groundwater level. The researchers therefore seek help from the local communities for data collection. Specific issues with formally recorded data are outline below:

There is only one source precipitation data within the study area, Dangila woreda. Although there are 8 other rain gauges outside the study area, they all situate at different altitudes, limiting the ability to make useful comparison. Gridded datasets could be an alternative source of data for precipitation. However, as their resolution which ranges from 0.25◦ to 1.25◦ is too coarse and comprise of a highly variable topography, it is likely that the results may be compromised too.

The past river discharge data faced significant inconsistency with gaps up to years. Additionally, two monitored river gauges within Dangila woreda are no longer functioning and their existing records were only inconsistently digitised. Furthermore, due to the lack of good quality data, there is often no information on the level of peak flood and its timing.

As for groundwater level, there are only very limited data on boreholes and groundwater available from formal sources. With community monitored data, there is now information on water table depth and recession.

How the community was involved?

The research team consulted the local community to identify suitable place for installation of rain and river gauges and well monitors. Consequently, the areas chosen were convenient for regular measurement by the community and allowed good quality data to be collected (Figure 3). (e.g. avoiding areas where trees intercepting rainfall from rain gauges and steeper channels where obvious river stage fluctuations could be clearly captured by stage board)

There were also regular workshops throughout the project to ensure the locals understand the results and the wider implication of the research. The level of engagement is maintained through feedbacks and many even actively noted down extra information (e.g. conditions and timings of peak flood) which is extremely helpful for improving the hydrological understanding of this data poor environment.

Figure 3. Photographs of monitoring in action. Left: Kilti river guage, middle: rain guage, and right: monitoring well.

How are the data judged?

The “Guide to climatological practices” (WMO, 2011) through the following tests checks the representativeness and accuracy of measured data:

• Format tests: error in dates and numbers
• Completeness tests: whether the data (or lack thereof) is significant to the study
• Consistency tests
• internal consistency checks: e.g. max rainfall > min rainfall
• temporal consistency checks: e.g. regular time interval
• spatial consistency checks: e.g. similar rainfall in neighbouring areas
• summarisation consistency checks: e.g. monthly values adds up to correct annual values
• double mass check: e.g. relationship between stage and discharge do not change if the data is consistent
• comparison with formally recorded values available

How successful was it? 

Figure 4 below clearly shows the community data performs much better than the gridded datasets (TRMM, ERA-Interim, NASA-MERRA) across all time periods in terms of correlation with daily rainfall from Dangila rain gauge and has higher average of correlation, 0.73, than the expected value of 0.68. Also, the bias (best if closer to 1) is the lowest for the community data (shown in Figure 5). 

Figure 4. Pearson's Product Correlation Coefficient (PPC) between formally recorded daily rainfall and different sources.

Figure 5. Bias between  formally recorded daily rainfall and different sources.

Although both river discharge and groundwater data lack formally recorded data for validation, they are deemed ‘highly satisfactory’ after several statistical analysis. It is also realised that community data could benefit from more frequent measurement to better capture the nature of flash flood.

Summary and my reflection

Through this exercise, the shallow groundwater system of this data poor area is much better understood. For example, areas with slow drops of groundwater level after rainfall events signifies significant baseflow, therefore a suitable site for potential groundwater extraction. The collected data also proved to be much more applicable than the global gridded data set for hydrological modelling on a local scale. Furthermore, the high correlation, 0.73, between collected and formally measured data also means that the historical data could be used to extend the length of the model.

While the idea of stakeholder participation has gained significant grounds in environmental management, to date there has been very few researches on the role of citizen science in quantitative environmental monitoring. This example showed that through early engagement with the local communities from the inception of the project to data collection and analysis, valuable data could be obtained easily by the everyone, especially in areas where no alternative data exists! As it is usually areas like this that could benefit most significantly through an inclusive and participatory hydrological research, this has huge implications for the data poor area worldwide!  Indeed, through the words of the Danila woreda people, they feel longer the ‘subject of study’ but rather important partners of the project. They take pride in their work from which other communities that face similar issues can learn and benefit. This is an example of empowerment of the local community, but also one that highlights the role scientists could play in connecting the disparity between science and local policy (Ridder and Pahl-Wostl, 2005).

The role of citizen science in hydrology: a review of the lack of hydrological data

From the last post, I brought up the idea that citizen science helps empower local communities in through their participation in data collection. What I did not mention was mobilising non-experts in the field of hydrology helps battle against the dearth of data on water resources ever since the 1970s, especially in the developing countries. Tanzania, according to the map producing by Wold Meteorological Organisation (WMO) (Figure 1), only have 1-50% of reporting rates. Additionally, the density of stations are clearly much sparse in comparison to those in Europe. This shows the importance of community monitoring schemes in Tanzania.

Areas with little data available often are the ones that suffer from poor management. With more data to better assessment the current hydrological conditions and project future scenarios, these areas will have the greatest potential for improvement through better mitigation and adaptation schemes (Walker et al 2016). Although there are data available from General Circulation Model (GCM), Regional Circulation Model (RCM) and reanaylsis rainfall product, the quality of the data is often hampered by the lack of observational data and thus modelling results suffer from inaccuracy and greater uncertainty (Symeonakiset al., 2009). Through community-monitoring schemes, it is possible to make up for the lack of formally measured data and provide a cheap but valuable source of hydrological time series data.

The lack of sub-Saharan Africa (SSA) hydrological data

In terms of rainfall, according to Washington et al (2006), on average there is only one met station every 26000km2. The density will need to increase by 8-fold to reach the WMO’s minimum recommendation. Many other studies (Pitman 2011; Washington et al., 2004) also pointed out that precipitation data had suffered greatly from the decreasing investment in the maintenance of weather stations. With the lack of maintenance, the number and density of rain gauges decreased quickly after 1970 (Willmott et al., 1994).

In terms of river discharge, only 2/5 of the river gauging stations around the world are functioning after 2003 (Tourian et al 2013) and this is due to the sharp decline in functioning river gauging stations is SSA (Walker et al 2016). Many experts believe that there is a dire need to better maintain and build more river gauging stations (Owor et al., 2009; Taylor et al., 2009).

For data on groundwater and hydrogeology, the situation is slightly different in the sense that there is no such sharp decline in data volume as there has been little historical observation in the first place! The understandings of aquifer and recharge mechanisms are often overlooked but are of significant importance for agricultural sectors in Africa in the future, especially under climate change where precipitation become more intense and uncertain (MacDonald et al 2012). 

Most existing data came from deep abstraction boreholes rather than the hand dug wells that are used daily by people in rural areas. More information and consistent time series data on the shallow hydrogeology, aquifer characteristics, recharge rates, flow regime and water quality of SSA is needed.

Given the current situation, we are indeed in need of greater hydrological data collection and one way to achieve this is through community monitoring schemes. However, as with any other form of citizen science, their validity is often called into question. Next week, I will discuss whether hydrological data collected by non-experts are useful in water resource assessment and management. 

The role of citizen in water resource assessment

This week’s blogpost will focus on the role of citizens in water resource assessment. Very often water resource assessments are carried out solely by experts (e.g. scientists and government employed consultants). This may lead to exclusion of local and often indigenous people in the process of decision making, rendering them on the receiving end of unwanted and negative impacts (examples). However, there have been successful cases of incorporating the local communities in the assessment of water resources. Not only did this allowed the contribution of local knowledge, it also empowered the locals in ways that have not been practiced before! Over the next few posts I will introduce examples of citizen science at work in the field of hydrology. This week, let’s focus on how the participatory monitoring programme in Tanzania has succeeded.

In Tanzania a large dam had been repeatedly proposed at Stiegler’s Gorge and it could have significant impacts on the floodplain lakes that support major socio-economic activities and livelihoods of the local communities (Figure1 and 2). This takes places against the backdrop of increasing dominance of developing countries such as China and Brazil in the water and hydropower industry in Africa (McDonald et al 2009). For example, in this BBC news article, it hints at China becoming the ‘Africa’s new colonial master’ as China infiltrates into industries ranging from cotton, shoe-making and construction of hydropower stations. According to Briscoe (2010), these emerging countries do not necessarily abide by the guidelines of World Commission on Dams (WCD) and pay less attention to the socio-economic and environmental needs of the locals.

 

Figure1. Map of the study area.

There are around 100,000 inhabitants likely to be affected by this development. Historically, during the wet season, the peak discharge allows the threshold that parts the lakes from the river (known as ‘Kingo’ Swahili) to be surpassed (Hamerlynck et al. 2011). However, with the proposed dam, the water source of the floodplain lakes will diminish. As the lakes provide income, drinking water and food source (fish) and are also of high cultural values with folklores that embed deeply in the spirituality of the locals (Duvial et al 2007), its socio-economic implications are significant. Furthermore, the adjacent forests which rely on the lakes are important biodiversity hotspot (Myer et al 2000) and provide fuelwood and wooden products for locals. With potential relinquished connectivity, little nutrients and organisms will be exchanged, further exacerbating the already deteriorating biodiversity.

In light of the potential impacts of the proposed dam on the wider communities and ecosystem, two approaches have been adopted to increase hydrological data collection. One is the use of sophisticated monitoring equipment (data loggers) funded 26.3 M$US by the Worldbank through the River Basin Management and Small-scale Irrigation Improvement Project (RBMSIIP) across 43 stations, the other is the implementation of a participatory monitoring system where locals are trained to do daily readings of stageboards across 8 sites. The study (Duvial et al 2013) shows the use of data logger have produced poor results of the while the data yielded from community efforts are much more consistent and of better quality. This is because there was a lack of funding for the maintenance and consistent download of data from the data logger while the latter through consistent workshops and feedbacks allowed efficient sharing of local and scientific knowledge. It informs both the locals and government of the significance of the flood and improved the relationships between the locals, local government and the national water ministry.

In sub-Saharan Africa, despite the increasing popularity of the IWRM concept, there remains a large gap that needs to be bridged between the theory and reality (Garcia 2008). One might wonder why this is the case. Well given that one of the main ethos of IWRM is to allow fair use of water resources, it follows that ‘equitable access to knowledge about the resource use options between different kinds of stakeholders’ is a prerequisite of IWRM. However in reality it is almost always the case that information is generated and shared asymmetrically, with powerful stakeholders such as the government, hydropower and commercial agriculture actors having the most data and information (Miranda et al 2011).  This case study shows by involving the less powerful stakeholders in the process of water resource assessment, a more just and equitable outcome is possible!

One small step towards ‘Integrated Water Resource Management’, one giant leap for the people in Tanzania indeed!

Are we dammed or damned?

As I mentioned in the previous post, the assessment of water resource may influence the direction of the water resource management. A prime example of this is the transition from large scale development such as dam construction towards a more integrated water resource management that recognises the social and economic needs of people as well as the natural environment. The latter no longer focuses solely on the volume/storage of water, it also pays attention to the demands and distribution of water. Furthermore, the environmental flow regime of natural habitats is also recognised under such a framework. This could be greatly attributed to the work many scientists have done in exploring the often not-so-obvious effects of dam constructions. Today in this post, I would like to focus on the hydrological and ecological impacts of dams in Africa through three case study: Itezhi-tezhiDam on Kafue River, Tiga and Kafin Zaki Dam and Challawa Gorge in theHadejia-Nguru river basin and lastly, the small scaled dams in South Africa.

The impacts of the dams on the hydrological regime and flow have been proven in all three locations.

For the Kafue River, the unregulated historic peak and low flow would occur between April and May and between October and November respectively. However, after the installation of the Itezhi-tezhi Dam, the natural hydrological regime has been compromised. The once gradual change in the volume of discharge had turned to episodic increase of flash flow released by the dams. As soon as the dam stop releasing water, the flow runs much lower than historic value. The number of month in which inundation takes place also increases. According to Howard and Williams(1982), discharge greater than 170 cumecs will overcome the embankments and lead to inundation of the floodplain. As can be seen in Figure1, the flow regime curve shows that the area downstream of the Itezhi-tezhi dam now have average flow higher than the threshold capacity of the channel between June and October, a period historically associated with low flow.

Figure1.

Monthly mean discharge of the Kafue River before (solid triangle) and (empty circle) after dam construction. 

For the Hadejia-Nguru river basin, similar situation is also observed due to the construction of dams and a series of irrigation schemes. According to the analysis, if the construction of Kafin Zaki Dam is completed and operated with the aim of providing irrigation to 84000 ha of agricultural land, the discharge downstream would decrease by 80%. This would effectively lead to similar level of drought experience in the 1980s. This would consequently lead to a rapid diminishing level of groundwater storage. Furthermore, the goal of sustaining the proposed 84000 ha of irrigation would not be viable during the 1970s and 80s according to the model simulation. As opposed to the large scale irrigation scheme mentioned in the two previous example, it is also shown that small scales dams with high spatial densities could have significant impact on hydrological regime and reduction on riverflow as well.

One common theme that runs across all example is the shift away from the natural hydrological regime. This has great ecological impacts on the environment and their biota. For example, due to changes in flow disturbance and extended period of inundation in the Kafue river and floodplain, alien invasive woody species such as the Mimosa pigra outcompetes the native aquatic species such as Echinochloa stagnina and Oryza longistaminata. Within a short 7-year period since the commissioning of the Itezhi-tezhi Dam in 1978, the infestation of Mimosa had increased by 50-folds from 2 ha to 100ha. Its extent spread from the head stream to the downstream floodplain in the process. As a keystone species with great potential to alter the nutrient energy flow within the ecosystem through trophic cascade, this is certainly a red flag for the water management practice in the region. Similarly, due to changes in the volume of flow and the time at which it happens, there is imminent threat to the Hadejia-Nguru wetland as well. However, in this case, it is due to the reduced wet season inundation that lead to the degradation and diminishing extent of habitat. Furthermore, the reduced quality of aquatic environment in South Africa caused by the high densities of small dams was shown to have benefitted the opportunistic taxa of macroinvertebrates that are better adapted to slower currents and higher disturbance and pollution. Overall, the construction of dams and its operation have led to multi-faceted on the regional ecology.

Another commonality among the three case studies is the need to strengthen hydrological monitoring. According to Mumba and Thompson (2005), more data is needed to distinguish the impact of climate change and operation of Itezhi-tezhi dam. As for the Hadejia-Nguru river basin, the overall quality of hydrological data has deteriorated significantly due to the lack of maintenance of hydrometric stations (Thompson and Hollis, 1995). Sukhmani et al (2010) also call for consistent assessment of environmental water requirement and this requires integration of reliable and representative data.

To sum up, the call for a better water resource management needs to be met by reliable water resource assessment, which in turn relies on the data. It has been used successfully by scientists to explore the negative impacts of dams.

Why Water Resources Assessment? (4) For the world beneath us is also complex

In times when the temperature variation and hydrological cycles become intensified, rendering the surface water supplies more unpredictable, it makes sense to put a greater focus on groundwater as part of the WRA. According to Taylor et al 2013, in vast region of semi-arid and arid Africa, people could only reliably source their water from underground due to the ephemeral nature of river flow. Without groundwater, it is very difficult for people to obtain water that is drinkable or potable. In addition, as they could be accessed by simple hand-dug well, they are much more economically affordable than buying bottled water.

But given the complexity of both physical and human landscape in Africa, is the exploitation of groundwater resources a cure-all panacea for the lack of water? The answer, as always, would be both yes and no.
According to MacDonald et al (2012), An estimated 0.66 million km3 of freshwater capacity have been found in Africa, with the reserve being most concentrated in countries such as Lybia, Algeria and Chad in Northern Africa (See Figure) . To put this into perspective, this is around 30 and 20 times the volume found in precipitation and lakes above ground respectively (Shiklomanov and Rodda 2003)!

Figure1. Map of groundwater storage in Africa.

What is more astonishing is despite an approximate 9-fold increase of abstraction volume in Makutapora Wellfield, the aquifer is not depleted. Taylor et al (2013) suggests that this could be related to the episodic recharge events that replenish the aquifer. Their results show that a non-linear relationship exist between the intensity of rainfall and groundwater recharge (see Figure2). Therefore on one hand, although climate change makes surface water supplies more unpredictable, on the other hand, it leads to more frequent and intense rainfall, which in the long run, could help replenish the groundwater and provide an alternative solution to the lack of freshwater.

Figure2. Scatter plot of rainy season rainfall against the volume of groundwater recharge. 

So that was Mr.Brightside talking, now let’s turn our attention to some other aspects of exploiting and utilising groundwater resources. According to both Giordano (2006) and MacDonald et al (2012), there are many physical and social constraints to this.

To be able to exploit groundwater, there needs to be sufficient yield of water extraction and this varies depending on its purpose. For example, to support domestic usage in a rural community, a simple handpump with a supply greater than 0.1 ls-1 is enough. The requirement rises to at least 5 ls-1 in both urban settings where its population is more concentrated and growing at a much faster rate and in areas of small scale irrigation scheme. Furthermore, for large scale commercial irrigation schemes, it could be upto 50 ls-1 (e.g. in the US).

Some areas, although store significant volume of water, they could not possibly be extracted at rates that meet the requirement for two reasons. Firstly, the yield also faces the issues of very high uncertainty as illustrated by Figure 3(a) and (b) that shows the possible range of productivity with different geological environment in Africa. This means the government and investors will be more reluctant in developing a new drill. Secondly, as the depth of the groundwater increase, so does the cost of development for drilling. Figure 4 shows both the depth and the likely interquartile range of aquifer productivity across Africa. Its uneven nature means although most areas are able to afford installing handpumps due to the shallow nature of groundwater levels, the largest reserve situated in northern Africa faces issues of extraction due to its depth of more than 250m and the fact that it situates far from site of usage (e.g. cities or intensive agricultural schemes). Also, there is limited area outside of large sedimentary basins with groundwater extraction rate of higher than 5 ls-1. The authors therefore concluded that to ensure a more successful groundwater exploitation, the development plan should be predicated on a very detailed knowledge of local groundwater conditions.

Figure3. (a) Range of aquifer productivity and (b) the underlying geology of Africa

Figure4. Map of estimated depth to groundwater and aquifer productivity in Africa.

As always, we need to have a better understanding of the hydrological system. How? WRA!

Why Water Resources Assessment? (3) For the world is complex

Last post covered the economic justification for WRA. The water resources in Africa is highly unequally distributed. Factors such as the movement of the Inter Tropical Convergence Zone (ITCZ), huge variation in surface relief, and intensification of climate change give rise to a very complex distribution of water resources, not to mention how this could be further complicated by the human landscape. In this post, we turn our attention to the physical climate and conditions of the continent Africa. 

Logically, when considering the input of water into a system, we think of the precipitation. In Africa, it is governed broadly by the movement of the ITCZ. This is supported by figure1 below which shows a rough latitudinal symmetry in the distribution of annual rainfall across Africa. The mechanism behind this pattern is as follows:

• The unequal heating of the Earth by the Sun causes atmospheric pressure gradient.
• This creates movement of air that flow from high to low pressure, leading to the formation of atmospheric cells. (See an animation here for representation)
• Where warm air meets and rises, the moisture carried by the air condenses once it becomes saturated in higher elevation, leading to rainfall. 
• The band of rainfall migrates up to the Tropic of Cancer in summer and down to Tropic of Capricorn. (See Figure2 and an animation here) 

This means that areas that are constantly within the zone of ITCZ will have higher rainfall and those that are covered by ITCZ once a year receive less rainfall.

Figure 1. The average annual precipitation in Africa (mm).

Figure 2. The movement of ITCZ.

The topography of the Africa continent further complicates the distribution of water. As Figure 1 shows, the centre of the continent receives the highest annual rainfall whereas in the east it is much lower. This is due to the presence of the East Africa Rift System (also known as the High Africa) that led to the formation of orographic rainfall and rain shadows. Figure 3 shows the elevation level across Africa. 

Figure 3. The elevation level in Africa (m).

The topography not only affects water resources availability in terms of the formation of rainfall, it also influences how much water will be taken out of the system via evaporation. It is known that generally the lower the elevation, the higher the temperature, and therefore the higher the potential evapotranspiration (PET). Coupled with climate change which influences the amount of rainfall and evapotranspiration, this could have a huge impact on the availability of water resources in southern Africa where its discharge has one of the highest coefficient of variation in the world (i.e. very variable.). With a 10% drop in prepcipitation, it reduces the river discharge by 17 to 50% (de Wit and Stanklewlcz 2006). Li et al (2015)'s climate projections predict an increase in both runoff and ET in eastern part of Southern Africa and a decrease in runoff in its  driest region e.g. Kalahari Desert, Namibia, southwest of South Africa and Angola. With such spatial variability in both rainfall  (the input) and PET (the output), the consequent river discharge also becomes more uncertain.

In short, after taking into account of factors such as the seasonality of ITCZ, topography and climate change within Africa, we may see the water available is much complicated and uncertain than we imagined. To be able to manage this uncertainty and risk of drought or flood, it is best to carry out a comprehensive WRA.