Water Scarcity Risk

In the classical approach to water scarcity or drought risk assessment, vulnerability factors are combined with information on hazard and exposure to assess drought risk (see Figure). The magnitude of a drought event, the exposure and vulnerability information together determine the impact of that specific drought event. In other words, the impact of a drought event is determined by hazard x exposure x vulnerability. Before the risk levels are computed, the watergap is reclassified and the proxy values for exposure and vulnerability are normalised. Finally, the risk levels are rescaled between 0 (very low, green) and 9 (very high, red). As a result, the presented water scarcity risk levels are relative risk levels within the basin.

In WaterLOUPE, water scarcity risk is expressed by risk level categories (low risk to very high risk). These categories are estimated using a combination of the severity of the watergap (see sections 2.1-3) and proxy values for exposure (e.g. GDP, km² agricultural area) and vulnerability (e.g. population below poverty line, GDP per capita). In case a specific risk category does not occur in a sub-basin, it is assigned a risk level of -1 (grey). More information about exposure and vulnerability can be found in section 2.4.

Reclassification watergap

Once the watergap is calculated, we reclassify it in values between 0 and 1. This reclassification is done based on the average watergap of the period of analysis according to the following method:

• If a given month has a negative watergap (i.e. scarcity), then watergap = 1 = very high hazard
• If a given month has a positive watergap smaller than the 10 percentile watergap for the period of analysis for that given basin, watergap = 75 = high hazard
• If a given month has a positive watergap > than the 10 percentile and < than the 25 percentile watergap of the period of analysis for that given basin, watergap = 0.5 = moderate hazard
• If a given month has a positive watergap >than the 25 percentile but < than the median watergap of the period of analysis for that given basin, watergap = 25 = low hazard
• If a given month has a positive watergap > than the median watergap of the period of analysis for that given basin, watergap = 0 = very low hazard

Data use policy

For the WaterLOUPE risk assessment data about hazard, exposure and vulnerability is required for each sub-basin. In many cases, local data is not available for all aspects of the water security risk assessments. Hence, national data or global data sets are consulted to supplement the local information. The data use is prioritized according to the following rules:

1. If local data is available for the appropriate time window, this local data is validated and used. Often rescaling of the data is required before it can be used for the risk analysis.
2. If local data is not available, but national data is available for the appropriate time window, the national scale data is validated and used after rescaling to local levels.
3. If no local or national data is available, output from the global water model PCR-GLOBWB is used. This model output is available at monthly time-steps and a spatial scale of 10x10 km. Important here that the output information is validated by local information and knowledge, before it is used in the risk assessment computations.

References

• Assessing water related risks to the industry and other stakeholders in 2 basins in Colombia. Deltares report (2017)
• Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability (2016)
• Global inventory of drought hazard and risk modeling tools. Deltares report (2018)
• Documentation global water model PCR-GLOBWB.
• Comparative Assessment of Drought Hazard and Risk Modeling Tools (2018)

Water demand is the sum of industrial, domestic, and agriculture (livestock and irrigation) water demand.

References

Assessing water related risks to the industry and other stakeholders in 2 basins in Colombia (2017)

Watergap = water demand – water availability

For the total basin and the sub-basins the current and future water availability and water use were computed. This gives a quantitative estimation of current natural water availability as well as water use by the different sectors (irrigation, domestic, industry, and livestock).

With this information we calculated a water balance to identify the watergap per sub-basin and per month for three 10-year periods: 2010-2020, 2020 - 2030, 2030 - 2040, and 2040 - 2050.

Local climate scenario

For the purpose of WaterLOUPE future water shortage risk calculations, a RCP climate scenario was used. 

Local socio-economic scenarios

Based on the narratives for the socio-economic scenarios, changes of indicator values of exposure and vulnerability of the main sectors / user groups were deducted for the local situation of each sub-basin. This provides information on the impact of the different SSPs on water use.

References

• Climate adaptation Colombia. Climate data scaling and analysis of the Magdalena basin (2014)
• Building global water use scenarios (2016)
• Assessing water related risks to the industry and other stakeholders in 2 basins in Colombia focussing on water scarcity (2017)

Exposure

Exposure to drought comprises all assets and sectors located in a drought-prone area. Examples of sectors that are susceptible to droughts and are relevant to include as exposure in a drought (risk) assessment are: agriculture, energy and industry, drinking/domestic water supply, navigation, ecosystems, tourism, forestry, aquaculture and fisheries, and the financial sector (investors, insurances, asset owners).

In a drought or water scarcity risk assessment it is important to collect data on exposure characteristics (proxies) that will influence the magnitude of the potential impact of the drought or water scarcity. Population relying on each sector (for income, food supply, water and electricity supply, etc.) and the economic value of each sector are relevant exposure characteristics to determine the impact of drought for all sectors. For example, the larger the share of exposed GDP, the larger the potential impact of a drought on the economy of a country.

Vulnerability

The magnitude of the impact of a drought or water scarcity event depends on the vulnerability of the exposed assets and sectors. Here, vulnerability can be referred to as the predisposition of assets or sectors to suffer adverse effects when exposed to a drought event. The level of vulnerability to a drought or water scarcity event is determined by the intrinsic characteristics of the asset or sector. For example, certain crop types are more vulnerable to droughts than others; and proximity of a drinking water plant to the coast makes it more vulnerable to salt intrusion during a drought. Therefore, it is important to collect the intrinsic exposure characteristics for the asset or sector as addressed in the exposure section above. In case such detailed information is not available, vulnerability can be assessed in a more generic way in which a distinction is made between three categories of vulnerability indicators: social, economic and infrastructural indicators. For each of these indicators proxies have been identified to quantify the level of vulnerability:

• Economic vulnerability can be quantified by proxies like energy consumption per capita; agricultural value added (% of GDP); GDP per capita; poverty headcount.
• Social vulnerability can be quantified by proxies such as the percentage of the population below poverty line; literacy rate; improved water sources; life expectancy at birth; population ages 15-64; refugee population; government effectiveness; human development index; disaster prevention and preparedness finances; conflicts.
• Infrastructural vulnerability can be quantified by proxies like agricultural irrigated land; % of retained renewable water; recycling ratios; irrigation efficiencies; road density; age of the infrastructure.

Selected proxies for this basin

To quantify te levels of exposure for each risk category, the following proxies were selected: percentage areas of land use types, population density and personal consumption expenditure or gross domectic product (GDP). This selection of proxies was based on data availability and discussions during the stakeholder workshop.

To quantify te levels of vulnerability for each risk category, the following proxies were selected: personal consumption expenditure or gross domectic product per person (GDP per capita), percentage of rural population, percentage of the number of people whose income falls below the poverty line (poverty rate), percentage of the number of people who live in extreem poverty (extreme poverty rate), percentage of the number of people that are aged below 15 (population below 15). This selection of proxies was based on data availability and discussions during the stakeholder workshop.

References

• Assessing water related risks to the industry and other stakeholders in 2 basins in Colombia. Deltares report (2017)
• Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability (2016)
• Global inventory of drought hazard and risk modeling tools. Deltares report (2018)
• Exploring drought vulnerability in Africa: an indicator based analysis to be used in early warning systems (2014)