Evaluation of In Situ Rainwater Harvesting as an Adaptation Strategy to Climate Change for Maize Production in Rainfed Africa
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Stabilizing smallholder crop yields under changing climatic conditions in sub-Saharan Africa will require adaptation strategies focused on soil and water management. Impact studies of climate change on crop yields often ignore the potential of adaptation strategies such as rainwater harvesting (RWH). While RWH is bringing benefits to agricultural systems today, it is still unclear which regions could increasingly benefit from RWH under changing climatic conditions. Here we employ a continental scale modelling strategy using the latest CMIP5 data and explicitly take into account design factors of RWH to show that it is a valuable adaptation strategy to climate change in Africa for maize (Zea mays L.). We find that RWH can bridge up to 40 % of the yield gaps attributable to water deficits under current conditions and 31 % under future (2050s) climatic conditions during the main growing season for maize, hence providing an alternative to irrigation from scarce or inaccessible groundwater resources. RWH could increase maize yields by 14–50 % on average for the 2050s across Africa, by bridging water deficits. While in situ RWH strategies show great biophysical potential as an adaptation strategy to climate change, there remain locally specific barriers to their adoption, which will need to be addressed to ensure their successful implementation at a larger scale.
KeywordsRainwater harvesting Climate change adaptation Climate change impacts
Rainfed agriculture remains to this day the predominant form of crop production in sub-Saharan Africa, with at its highest 21 % of the total cropland harvested irrigated in Southern Africa, and a meagre 1 % irrigated in West Africa (Portmann et al. 2010). The expansion potential for irrigation is very limited and hence solutions to increase food security and decrease poverty will have to rely on alternative water management strategies (Rockström and Falkenmark 2015). With a changing climate, dryland African farmers who subsist from rainfed agricultural systems will have to cope with increased risk arising from more frequent extreme events and poor intra-seasonal rainfall distribution (Barros et al. 2014). Since rainfall patterns are the main factor steering crop productivity in Africa (Muller et al. 2011), these changes will be detrimental to food production (Cline 2007). However, the potential (and current) use of adaptation strategies to overcome these challenges is rarely taken into account in impact studies. Several adaptation measures are being promoted to cope with a changing climate, such as the use of different crops or crop varieties, soil conservation, changing planting dates, and irrigation (Bryan et al. 2009), but these may not all be viable choices for smallholder farming either due to their high costs, technical restrictions, or even cultural limitations (Adger et al. 2012).
In areas such as the Sahel, where it is estimated that only 10–15 % of rainwater is used productively for plant growth (Breman et al. 2001), rainwater harvesting (RWH) could help mitigate the impacts of climate change on crop production. In situ RWH strategies, such as planting pits or stone bunds implemented at the field level (Online Resource 1), act to shift a fraction of surface runoff water to productive purposes by storing water in the form of soil moisture (Rockström et al. 2002). This entails that water is made directly available to crops, and does not require being re-routed using pumps. They are not aimed at directly improving water use efficiency, but rather at reducing the variability in potential and actual crop yields (Fox and Rockström 2000). By increasing the water holding capacity of highly degraded soils, RWH can also reduce crop damage due to soil degradation by water erosion. Moreover, RWH reduces the susceptibility of crops to the adverse effects of frequent dry spell events (Barron et al. 2003; Rockström et al. 2002), and has the ability to reduce inter-seasonal crop yield variability associated with erratic climatic patterns.
Numerous studies have investigated the siting of RWH systems under current climatic conditions (e.g. Jasrotia et al. 2009; Kadam et al. 2012), but most fail to assess the performance of these systems under changing climatic conditions. Moreover, they often provide data-intensive, site-specific, and crop-independent analyses, which can be inadequate to inform national-level policy making. While we know that RWH can bring benefits to rainfed agricultural systems today, it is still unclear which regions could increasingly benefit from RWH under changing climatic conditions.
Here we quantify, at the continental scale, the potential of RWH to reduce water deficits experienced by a maize (Zea mays L.) crop under present and future climate projections for the 2050s across Africa for increasing radiative forcings (RCP8.5). Under this scenario, the 2050s would be the first period where climate would depart from its current variability, and therefore lead to unprecedented environmental conditions (Mora et al. 2013). Maize is the most widely grown crop in Africa, especially in Southern Africa where it represents 50 % of the harvested area (Portmann et al. 2010), and is one of the crops most often found to be produced with the help of in situ RWH. Its production is expected to continue to grow in the future. Using a grid-based empirical approach based on freely available datasets, including the latest data from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we establish water deficits experienced by maize on a monthly basis. Then, we evaluate the amount of water that can physically be harvested within each grid cell in Africa. Different than previous analyses, our analysis explicitly takes into account local biophysical characteristics to evaluate RWH capacity, as opposed to assuming that a constant fraction of runoff can be harvested at any location (e.g. Rost et al. 2009). Finally, we estimate RWH benefits on crop yields under current and future climatic conditions.
2 Materials and Methods
2.1 Climate Input Data
A simple empirical approach to the determination of RWH potential was developed based on freely available datasets. The aim was to provide a spatially-relevant overview of agricultural water management requirements for national-scale policy-making, in regions where higher-resolution data can be scarce. A schematic representation of the methodological process is presented in the Online Resource 2.
2.2.1 Estimating Crop Water Requirements
Cropping calendar datasets based on typical national and sometimes sub-national planting and harvest dates for the 1990s or early 2000s (Sacks et al. 2010) were used to produce weighed monthly crop evapotranspiration values based on the crop coefficient (Kc) at the four crop growth stages (initial, crop development, mid-season, late season). The cropping calendars were also used to estimate monthly values of the yield response factor (Ky) (c.f. Section 2.2.3), for yield impact evaluations. The yield response factor is widely used in crop models and irrigation planning. Each crop growth stage has differing sensitivities to environmental stresses (e.g. grain filling and flowering, which occur mid-season, are the most sensitive stages to water stress), which in turn affect the Kc and Ky values. Standard Kc and Ky values for maize (Online Resource 2) were obtained from the FAO (Allen et al. 1998).
Subsequently, monthly water deficits were established from the difference between estimated monthly crop water requirements (ETc.) and the monthly rainfall amounts having a probability of occurrence of 67 % (i.e. minimum rainfall expected 2 years out of three). The latter is what is termed “design rainfall” when determining the sizing of RWH systems. The “design rainfall” accounts for significantly greater inter-annual variability present with rainfall, than with solar radiation or temperature used to estimate crop water requirements.
2.2.2 Estimating Rainwater Harvesting System Design Requirements
Here, the runoff coefficient is defined as the fraction of surface runoff to precipitation. A conservative value for the efficiency of in situ RWH systems was set to 0.6, but it can reach up to 0.75 for such short slope catchments (Critchley and Siegert 1991). The efficiency factor takes into account the fact that not all harvested runoff can be used effectively by crops. The C:CA was calculated on a month-to-month basis, for both the historical and the future periods.
The maximum monthly value of the C:CA ratio required to fully bridge crop water deficits was determined. Fully bridging those deficits may require an excessively large catchment area, but farmers in arid environments already compensate by using very low cropping densities (e.g. Bationo et al. 1992). In our study, we vary spatially the C:CA ratio with respect to aridity, in order to integrate this reality. Hence, the use of larger catchment areas in those conditions does not necessarily reduce the availability of arable land for agricultural production. The aridity indices were determined using the De Martonne Aridity Index (which ranges from 0 for very dry to 100 for very humid environments) (de Martonne 1927) for both the historical and future period.
Assumed maximum allowable C:CA ratios by aridity zone
Maximum allowable C:CA ratio
The actual evapotranspiration (ETa) is equal to the design rainfall where there is no RWH. In the case where we use RWH, the C:CA ratios adjusted for aridity were used to estimate the amount of water actually harvested, which was then added to the design rainfall to obtain the total monthly ETa values.
2.2.3 Estimating Impacts on Crop Yields
2.3 Methodological Limitations
As in any modelling study, the approach taken to evaluate RWH potential has inherent uncertainties. For instance, the selection of Kc and Ky can have a large impact on the estimation of crop water requirements. Standard values were selected, as a coarse-scale assessment of water requirements was conducted both spatially and temporally. This approach allows us to get a quick overview of which areas might suffer from greater water deficits, and is deemed essential to make climate-based agricultural water analyses relevant (Barron et al. 2003). The use of cropping calendars at a coarse resolution may lead to some regional anomalies in the results, especially at the borders between countries due to national-scale input data. Other uncertainties arise from GCM data. While we acknowledge that not all models produce reliable surface runoff from their land surface component (e.g. MRI-CGCM3), we chose to use gridded runoff data generated through GCMs as they guarantee a closed hydrological cycle (Weiland et al. 2012). We found that for the three models selected the runoff coefficient remained within reasonable bounds over rainfed Africa (i.e. between 0.05 and 0.3, Online Resource 2).
Furthermore, using a coarse-scale empirical approach has the disadvantage of ignoring a wide range of processes involved in crop production, such as the increased nutrient use efficiency associated with higher water availability. This can lead to a significant underestimation of the potential of RWH to increase crop yields. This approach also ignores small-scale hydrological processes (e.g. crusting of soils in the Sahel), local socio-economic conditions, and the impact of daily rainfall variability.
Finally, the use of a field-scale equation to evaluate RWH potential with climate data at a much coarser resolution could lead to inaccuracies in the results. That being said, obtaining data to accurately model field-scale hydrological processes is impractical for a continental-scale assessment of RWH potential. The next section will also demonstrate that despite scale discrepancies, estimated C:CA from the coarse scale CMIP5 data is representative of the design requirements of reported local techniques.
3.1 Rainwater Harvesting Design Requirements
Here, the selected GCMs agree in a number of areas on the magnitude and direction of change in required cropping densities and C:CA ratios by the 2050s. Southern Africa is likely to be the most adversely affected region, while the Sahel does not see significant changes in RWH design requirements despite some projected increases in precipitation (c.f. Fig. 1). Areas of full agreement between models include Tanzania and Mozambique, while two out of three models show the need for greater C:CA ratios over Zambia and Zimbabwe.
3.2 Mapping Crop Water Deficits Over Rainfed Areas
3.3 Stabilizing Crop Yields Through RWH
Generally, the fraction of the yield gap caused by water deficits that can be bridged through RWH decreases by the 2050s, in regions where that yield gap increases. However, where aridity shifts to a higher aridity zone into the 2050s, the allowable catchment areas can be increased, leading to an increase in the benefits arising from the use of RWH. Overall, maize yield gaps which could be bridged through RWH range on average across Africa from 37 to 47 % for the 1990s, and decrease to 28–36 % for the 2050s (Fig. 5). Overall, RWH could maintain its ability to bridge a large part of water deficits in the future, and partially mitigate negative impacts of climate change.
3.4 Prioritizing Areas for RWH Implementation
Field-level experience has shown great potential for RWH to stabilize crop yields in otherwise harsh environmental conditions (e.g. Rockström et al. 2002; Sawadogo et al. 2008). At a larger scale, we found that the ability of RWH to bridge water deficits and to stabilize crop yields in Africa is projected to continue in the medium-term (2050s) under RCP8.5, despite some regions becoming more vulnerable. Where RWH is projected to perform more poorly in the future, irrigation should also be considered to adapt to climate change. However, in regions where groundwater resources are limited (MacDonald et al. 2012), RWH could still provide supplemental water for crop production by smallholder farmers.
In the semi-arid tropics and arid environments, RWH has already played an important role in stabilizing crop yields by mitigating the negative impacts of high evapotranspiration. However, those regions are projected to experience a higher frequency of lethal high temperatures which will likely not be mitigated by RWH. Hence, areas seeing a decrease in water deficits between the 1990s and the 2050s should not always be interpreted as potentially benefiting from climate change. This is particularly true in the Sahel, where an increased frequency of lethal high temperature events could have devastating effects on food production (Battisti and Naylor 2009).
While this study focused primarily on bridging water deficits, it is important to note that in several areas, RWH is also used in combination with nutrient management strategies (Rockström et al. 2002; Zougmoré et al. 2003), and can promote fertilizer utilization in areas of low adoption (Wakeyo and Gardebroek 2013). In Sahelian environments, soil fertility improvements could increase water use efficiency by three to five-folds (Breman et al. 2001). Moreover, RWH systems allow for the retention of water, for the conservation of nutrients through a reduction in soil losses associated with water erosion, and an overall reduction in risk to crop production. Hence, increases in yields associated with RWH go far beyond the simple bridging of the yield gap caused by water deficits, and the estimates presented here are only a fraction of the true benefits RWH can have on increasing crop yields in African drylands. There is still a need for higher spatial and temporal resolution studies to capture intra-seasonal distribution of rainfall and use of fertilization on the efficiency of RWH systems, amongst other factors (e.g. Pandey et al. 2013). In a context where we are unable to provide farmers reliable and consistent long-term inter- or intra-seasonal projections of changes in the climate, another possible benefit of RWH could be to help deal with precipitation variability by increasing the flexibility of cropping calendars. Specifically, RWH could extend the growing period by concentrating surface runoff associated with isolated rainfall events early or late during the season, and reduce the risk associated with the heavy reliance on those first few rains to determine when farmers are able to plant their crops.
Finally, one of the objectives of this study was to provide the “big picture” of the potential of RWH to stabilize crop yields, and reduce dependence on groundwater resources. In a context where African agriculture needs to be more productive to feed its population, these RWH benefits could be non-negligible. While agricultural development discourse has been heavily focused on the successes of the Green Revolution in Asia (and the expansion of irrigation), we still need to take into account the strikingly different situation of Africa today. If it is possible to bridge a minimum of 30–40 % of yield gaps associated with crop water deficits simply with in situ RWH, the questions of energy requirements to access water, costs of implementation for wells or pumps, or overall low adaptive capacity, all become less of an issue for smallholder farmers. Despite in situ RWH strategies having the advantages of often being indigenous techniques, affordable, and widely applicable for smallholder farming, barriers to their adoption should be better understood to ensure their long-term sustainability (Pachpute et al. 2009).
This study set out to use GCM outputs to evaluate RWH potential, including the lesser-used surface runoff variable, and has shown promise towards providing useful information for adaptation planning at the national level. Indeed, the information provided here can be used to prioritize areas for RWH implementation and identify where complementary adaptation strategies might be necessary to fully address climate change impacts on crop water availability. Despite high levels of uncertainty associated with climate change projections, there is a need for smallholder farmers in sub-Saharan Africa to start coping more effectively with current climate variability. RWH represents a partial technical solution to the much more complex challenge of food insecurity, but offers a way to increase resilience to climate variability. Indeed, we find that RWH could bridge 31 % of yield gaps attributable to water deficits under the projected climatic conditions of the 2050s, and increase maize yields by 14–50 % on average across Africa. Yet, the adoption rates of simple and often endemic technologies such as RWH stagnate without the proper training support of local governments and NGOs. RWH, especially in situ methods, offer the competitive advantage of requiring minimal financial, environmental, and social investments over other adaptation strategies such as the development of new drought-resistant crop varieties. A good understanding of local limitations to the adoption of RWH will be necessary to make them successful across the continent.
This study was funded by a University of Leeds FIRS scholarship, and WAHARA (EU 7th FP, grant no. 265570). We would also like to acknowledge the support of James Watson, William Brown, and Daniel Lacasse in contributing lines of code for the pre-processing of the CMIP5 climate data.
S. Lebel, P.M.F., and L.F. all contributed to the development of the original research idea. L.S.J. wrote the code for the pre-processing and regridding of the CMIP5 data, which was then adapted and used for the purpose of this analysis by S. Lebel and S. Lorenz. P.M.F. sourced the CMIP5 data. S. Lebel conducted the calculations. S. Lebel wrote the manuscript with significant inputs from L.F. and P.M.F.
- Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration - guidelines for computing crop water requirements. In: FAO (ed.) Irrigation and drainage paper., Rome, ItalyGoogle Scholar
- Barros VR, Field CB, Dokken DJ, Mastrandrea MD, Mach KJ, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL, Niang I, Ruppel OC, Abdrabo MA, Essel A, Lennard C, Padgham J, Urquhart P (2014) Africa, climate change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel of climate change. Cambridge University Press, Cambridge, pp 1199–1265Google Scholar
- Cline WR (2007) Global warming and agriculture: impact estimates by country. Peterson Institute for International EconomicsGoogle Scholar
- Critchley W, Siegert K (1991) Water harvesting: a manual for the design and construction of water harvesting schemes for plant production. In: FAO (Eed.) RomeGoogle Scholar
- Doorenbos J, Kassam AH (1979) Yield response to water. Irrigation and Drainage Paper 33Google Scholar
- Elliott J, Deryng D, Müller C, Frieler K, Konzmann M, Gerten D, Glotter M, Flörke M, Wada Y, Best N, Eisner S, Fekete BM, Folberth C, Foster I, Gosling SN, Haddeland I, Khabarov N, Ludwig F, Masaki Y, Olin S, Rosenzweig C, Ruane AC, Satoh Y, Schmid E, Stacke T, Tang Q, Wisser D (2014) Constraints and potentials of future irrigation water availability on agricultural production under climate change. Proc Natl Acad Sci 111:3239–3244CrossRefGoogle Scholar
- Kadam A, Kale S, Pande N, Pawar N, Sankhua R (2012) Identifying potential rainwater harvesting sites of a semi-arid, Basaltic Region of Western India, Using SCS-CN Method. Water Resour Manage, 1–18Google Scholar
- Oudin L, Hervieu F, Michel C, Perrin C, Andréassian V, Anctil F, Loumagne C (2005) Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2—towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling. J Hydrol 303:290–306CrossRefGoogle Scholar
- Portmann FT, Siebert S, Döll P (2010) MIRCA2000; Global monthly irrigated and rainfed crop areas around the year 2000: a new high-resolution data set for agricultural and hydrological modeling. Global Biogeochem Cycles 24, GB1011Google Scholar
- Sacks WJ, Deryng D, Foley JA, Ramankutty N (2010) Crop planting dates: an analysis of global patterns. Glob Ecol Biogeogr 19:607–620Google Scholar
- Sawadogo H, Bock L, Lacroix D, Zombré NP (2008) Restauration des potentialités de sols dégradés à l’aide du zai et du compost dans le Yatenga (Burkina Faso). Biotechnol Agron Soc Environ 12:279–290Google Scholar
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