Workshop D1: Modelling the Nexus: Case Studies
Chaired by Aiko Endo
Presenting speakers :
Water stress is one of the three global risks of highest concern, according to the World Economic Forum (Wada et al. 2014 from Hoekstra et al 2014). Rapid human population growth, agricultural development, and fast urbanization promote the water demand worldwide and especially in the global south. On the African continent still more than 350 million people (UNESCO) lack access to clean drinking water. Hydropower dams and their reservoirs are one of the technologies to meet both, an increasing electricity demand and the need for clean freshwater resources.
In Africa, only 8% of the technologically feasible hydropower potential is currently exploited, yet an unprecedented boom in dam construction will more than double hydropower capacity within the next 10-20 years. For electricity production only, more than 200 large hydropower dams (> 1 MW) and reservoirs are currently under construction or planned on the African continent (Zarfl et al. 2015). However, hydropower development may come along with severe social, economic and ecological effects such as relocation of people, trans-boundary conflicts (Richter et al. 2010), fragmentation of river networks (Grill et al. 2015), spreading of water-borne diseases (Lerer & Scudder 1999), and changes in the natural flow, thermal and sediment regimes (Constantine et al. 2014). This causes the loss of habitats, restricts the movement of aquatic organisms, and alters or even eliminates biodiversity (Winemiller et al. 2016). There is an urgent need to systematically integrate the environmental and social impacts of future hydropower dams to support decision making in their construction and subsequent operation (Opperman et al., 2015). We have established a comprehensive and multidisciplinary network to scientifically address several of these concerns and to investigate the ecological, social and economic impacts of future hydropower dams in Africa. The results will be used to formulate recommendations for the sustainable construction and operation of hydropower dams and associated freshwater reservoirs.
One major concern in the operation and the planning of future reservoirs is the quality of the drinking water. Many tropical countries face toxic algal or cyanobacterial blooms (mass development) in drinking water reservoirs (Mowe et al. 2014), which is a recognized health hazard (WHO) for humans and livestock. Climate change and rising temperatures, as well as increasing nutrient inputs from agricultural soils prosper the growth of toxic cyanobacteria (Paerl & Otten 2013), so that African countries, especially in the Sub-Saharan region, will increasingly have to deal with the consequences of cyanobacterial blooms. Yet, no adequate monitoring program for toxic cyanobacteria, nor sufficient drinking water treatment management plans exist in those countries. We have identified high-risk regions for cyanobacterial blooms on the African continent and will identify their main driving factors in artificial reservoirs by using a combined approach of satellite data (Agha et al. 2012; Guanter et al. 2010) and field studies. The data will be implemented in the above-mentioned network and will help understanding the risk of toxic cyanobacterial blooms for drinking water safety in those countries.
Food production is of great importance to the government and the farmers in Iran and in QINA as well, although water scarcity is the main issue in the country. First, the government demands farmers to increase food production to strengthen food security. In order to achieve that, it has adopted policies to prompt farmers to increase crop production (i.e. wheat). Second, the farmers tend to cultivate as much as possible to gain more. This situation has put Iran in a water shortage crisis and groundwater level has been dropping down severely in aquifers all over the country.
Further groundwater abstraction has been banned by the government from 35 years ago in Qazvin plain but during these years not only the groundwater level has not been constant but also has been dropped especially in recent years. In this area water extraction from wells are not monitored in an appropriate way. As a result the farmers not only extract more water than their permission from their legal wells but also illegal wells are spread all over the area. The farmers have to consume energy to extract water from wells but as Iran is a great producer of oil in the world, energy cost is such low (because of the subsidies) that they do not have to spend a lot for water abstraction from their wells. In this example, water and energy are two main elements to produce food but there is almost no limit for the farmers to use them to cultivate crops. Thus water and energy are considered as abundant resources for the farmers to produce food.
This situation in Qazvin plain and actually all over Iran has worsen water scarcity while groundwater level dropdown in many aquifers has become a common issue. The farmers are not committed to save their resources and the governmental policies are not in a way to prompt them to be more self-organized to sustain their resources.
As a result we intend to analyze the relationship between water, food and energy policies in QINA and realize their effects on the level of self-organization through an agent-based approach. By this modeling approach we will be able to consider social and ecological aspects of a water resource system to evaluate what would be the result for the groundwater resources, if the farmers and the government paid more attention to water scarcity and energy consumption. To be more specific we want to see what would happen if water and energy consumption were more restricted through pricing or good monitoring practices.
This paper presents a tool for measuring drought risks in the Cuvelai basin in Angola and Namibia. The aim is to incorporate both meteorological and agricultural drought characteristics that impair the population’s ability to ensure food and water security. This so called Blended Drought Index (BDI) is capable of incorporating relevant parameters of water availability in the target area including spatial and temporal rainfall distribution, temperature and changes in storage. Therefore, the BDI is composed of the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSI) and the Standardized Precipitation Evaporation Index (SPEI).
Since ground measurements of hydro-climatic variables in the study area are sparse, station data are replaced by satellite remote sensing products (CHIRPS 2.0, GLDAS, CRU TS3.22). All indices were calculated by creating a moving sum time series of the monthly input variable, which was fit to a probability density function (PDF). The PDF was then transformed to a standardized normal distribution with a mean of zero and standard deviation of 1. Negative values indicate below normal conditions and therefore potential drought events. For validation, the BDI was compared to pearl millet yield, as the most common crop grown in the region. However, reliable data were scarce since they were limited to the years 1995 to 2007. Therefore, a second validation method was introduced, comparing BDI results to historical drought reports from newspapers and the international disaster database (EM-DAT).
The results give insights into the spatial and temporal occurrences of drought events between 1983 and 2010. The drought risk is highest in the eastern and central areas of the Cuvelai, as water availability in these regions varies more greatly over time. Furthermore, high BDI values correlate well with reduced millet yield (Pearson r = -0.67), showing that the impact of droughts on agriculture is represented well. Socio-economic drought impact, as depicted by reported droughts in the study area likewise corresponds with the BDI, especially for the long drought in 1987/1988. The Blended Drought Index is suitable to calculate drought risk in data scarce regions by using multiple satellite datasets. The risk of insecure conditions with regard to food and water can be estimated from the results but further insights into the socio-economic setting of local households are necessary to comprehensively characterize drought vulnerability. For this reason, the BDI is part of the Household Drought Vulnerability Index (HDVI) that is currently under development.
Target audience: We invite interested participants from all disciplines and at all career stages specially early stage PhD student and postdocs.
Date and time: Jun 16th, 13:15 – 15:00
Location: ZUK, Osnabrück, Room 3
- Aiko Endo