Climate Change Impacts on Water Availability and Use in the Limpopo River Basin

Zhu, Tingju; Ringler, Claudia

doi:10.3390/w4010063

Cited by 58 publications

(40 citation statements)

References 20 publications

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“…Southern African water resources are regarded as being highly affected by seasonal variability, a fact that is likely to be exacerbated by climate change (Kusangaya et al, 2014). Zhu and Ringler (2010) estimated a decrease in Limpopo streamflow by 2030 due to climate change, which is contradictory to studies that found increases of precipitation (Tadross et al, 2005) and runoff (Li et al, 2015) in parts of southern Africa, including vast parts of the Limpopo Basin.…”

Section: Introductioncontrasting

confidence: 38%

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Seibert

Merz

Apel

2017

Hydrol. Earth Syst. Sci.

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Abstract. The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study.1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated).2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments.3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships.4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts.

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Section: Introductioncontrasting

confidence: 38%

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Seibert

Merz

Apel

2017

Hydrol. Earth Syst. Sci.

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“…The Limpopo River basin is expected to face even more serious water scarcity issues in the future, limiting economic development in the basin (Zhu and Ringler, 2012). To apply this framework at the regional scale, a finer-resolution version of the global hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was adapted to regional conditions in the basin.…”

Section: P Trambauer Et Al: Identification and Simulation Of Past Hmentioning

confidence: 99%

Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa

Trambauer

Maskey

Werner

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finerresolution version (0.05 • × 0.05 • ) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05 • (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for MediumRange Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

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“…It will lead to decreasing precipitation rates and increase drought events [4]. Thus, water management and infrastructure changes have been expected to improve the situation if current climate conditions continue into the future [5]. On a global view, 70 % of the freshwater resources are used for agricultural purposes, and only 19 % for industrial and 11 % for domestic purposes (including drinking, washing, food preparation and sanitation) [6].…”

Section: Introductionmentioning

confidence: 99%

A wireless rainwater collecting, filtering, and storing system using a cell-phone

Cheng

Chiu

2018

MATEC Web Conf.

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Abstract. Because of the greenhouse effect, global climate considerably changes and will worsen the water supply situations in future. Also, as can be seen in traditional reservoir, the crisis of water lacking will exacerbate due to the reservoir sedimentation. In order to widen the storage of water resources, a design of portable rain-collecting system used for irritation and daily use for people is presented. To facilitate the monitoring and manipulating, a rainwater collecting and storing system with green energy/automation /monitoring/control function is established. Considering the electricity shortage in remote island/mountain regions, two kinds of green energy generators (wind electrical generator and solar-board electrical device) are built and linked with the system. Here, a rain detector installed onto the roof can actuate the rainwater collecting board to raise and to collect water when raining event occurs. For the purpose of water purity, water filter is also set at the entrance of the water tank. In order to efficiently store/use the rainwater, several water storage tanks in conjunction with ecological pool are preset and adjusted via the water level gauge sensors and the pipe's solenoid valve. To meet the weather-proof ability, PLC is adopted as the controller. Moreover, a human-machineinterface is login on the internet and remotely communicated with the cell phone.Consequently, a prototype of the cell-phone base automatic rainwater collecting and storing system is established.

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Climate Change Impacts on Water Availability and Use in the Limpopo River Basin

Cited by 58 publications

References 20 publications

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa

A wireless rainwater collecting, filtering, and storing system using a cell-phone

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