Because pyrethroids tightly bind to the soil, the most common transport mechanism off-farms and into nearby waterways is on suspended solids . While pyrethroids have a short half-life in aqueous solutions, one California study found that bifenthrin, a pyrethriod commonly applied to strawberries in the Central Coast and one of the pesticides that showed to be highly effective in Joseph and Zarate’s study on cabbage maggot control, has a half-life in soil solutions of 165 days . This means that the chemical will still likely be toxic coming off a field approximately a year later. By the time the chemical is detected in a waterway, the polluting strawberry grower might have moved, and the residual material coming off the farm would be the problem of the next grower. Under these circumstances, individual edge of field monitoring , or even individual groundwater monitoring , would not be as suitable a policy tool. The success of the 2012 Agricultural Waiver in dramatically curtailing two pesticides known to cause harm in local waterways are laudable. Threatening to put growers in tier 3 was an effective tool in discouraging farmers from using chlorpyrifos and diazinon. However, the unique sets of circumstances paving the way for growers to readily discontinue their use of the two pesticides in the region should not be overlooked. Regardless of tier 3 mandates and the Agricultural Waiver, growers’ opinions about both chemicals were lukewarm at best. As an increasing number of scientific studies published the negative impacts of both chemicals,flower harvest buckets there was a growing discomfort among growers in using pesticides that could likely cause harm to their workers and the environment.

Additionally, in the case of chlorpyrifos use on broccoli, the overall effectiveness of the chemical on pest suppression and crop health was uncertain, even in the cooler maggot-friendly climate. Brassica growers use chlorpyrifos only prophylactically, or as a preventative measure, and as one study suggests, one or even two applications of the pesticide could have little to no effect on cabbage maggot infestations . Additionally, differences in the fate and transport of organophosphate pesticides lent themselves to the policy tools employed in the Ag Waiver. For example, the threat of individual monitoring requirements is greater for growers applying short half-life and water-soluble pesticides, like chlorpyrifos and diazinon, because they could be identified as a discharger in a short time frame through water quality monitoring. This response would not be expected with nitrates or longer-lived, sediment-binding pesticides for several reasons. First, reducing the use of or finding a substitute for the valuable fertilizer would be difficult, if not impossible. Also, nitrates naturally occur in the environment, creating the added complexity of identifying which nitrates were naturally occurring and which originated from excess fertilizer application. A much more difficult task lies ahead for Central Coast water quality regulatory agencies. Unable to re-use the policy tools that worked so effectively in 2012, the Regional Board is forced to creatively assemble a new set of regulatory instruments to address the next set of chemicals rising to the fore. Among the many aspects of programs and tools the Board will need to consider is which best management practices to mandate or encourage, since best management practices to mitigate off-farm movement substantially vary with the chemical, class of chemical, and crop targeted.

The ability of Central Coast’s agricultural industry to continue to thrive economically and produce food for much of the nation while not polluting waterways will depend upon a more comprehensive management approach that encourages best management practices and integrated pest management systems. The latest regional inventory of dams in Africa shows that the continent includes almost 1300 large and medium size dams. The majority of these dams have been constructed to facilitate irrigation and to supply water to municipalities . Although only 6% of dams were built primarily for electricity generation, hydroelectric power accounts for more than 80% of total power generation in 18 African countries, and for more than 50% in 25 countries. A series of severe electricity crises and growing water needs have led many African countries to plan and build large dams during the last decade. In 2006 over 51 dams were under feasibility study or under construction in the continent. As such, dam construction appears to be central in the investment strategy for growth in the continent. However, the extent to which dam construction in Africa and elsewhere is a pro-poor strategy is highly debated while little evidence exists to guide policy. To our knowledge this paper is the first attempt to document the welfare effects and distributional impact of dam construction in Africa. Research on irrigation dams in India finds that districts located downstream from a dam experience an increase in agricultural productivity and a reduction in rural poverty . However in districts located upstream from a dam, agricultural productivity remains unchanged and rural poverty worsens.

The analysis on the impact of dams on agricultural productivity and welfare has been limited by the lack of long time series data on agricultural input and output and consistent data across several countries. In a recent paper, Strobl and Strobl use remote sensing techniques to investigate the impact of African dams on agricultural productivity. Although they use a proxy for agricultural productivity and different units of analysis Strobl and Strobl’s findings are consistent with those in Duflo and Pande. In this paper we take a different approach to measuring the benefits and distributional impacts of African dams. Firstly we use household surveys from which are constructed measures of the nutritional status of children 2 to 5 years old across 17 countries. Secondly, because the household surveys are linked to GPS data we can determine the location of survey clusters vis-à-vis dams at a fine geographical level. Lastly, our outcomes of interest – measures of the nutritional status of children – have the advantage of providing a net effect of dams that include both the effects through agricultural productivity and health. However our data is cross sectional and we rely only partially on the time series variation in dam construction to identify the effect of dams on child nutrition. While Duflo and Pande use administrative sub-entities as their unit of analysis, we follow Strobl and Strobl and use a spatial breakdown of Africa based on actual hydrological data to choose our units of analysis. We use HYDRO1k, a database developed by the U.S. Geological Survey’s Data Center,round flower buckets which divides Africa into 7131 hydrological basins. Each basin is assigned a Pfaffstetter 6-digit code which can be used to determine whether the basin is upstream, downstream or not related to another basin in the dataset. We combine this dataset with FAO’s African Dams Database to determine the number of dams within each hydrological basins and in upstream basins. A substantial proportion of dam construction in Africa was preceded by the establishment of river basin treaties and authorities which dealt with the management of water resources and encouraged the construction of dams. Strobl and Strobl’s work identify the boundaries of 59 basins where a treaty was signed. Our empirical strategy, following the approach in Duflo and Pande, exploits variations in dam construction induced by differences in river gradient across river basins within the same treaty basin to obtain instrumental variable estimates.

We find that while river basins located downstream from a dam benefit from it, children in basins where the dam was built are less well nourished. More specifically we find that children in river basins downstream from a dam are taller and heavier, while they are shorter and thinner in areas where a dam is located. Using these estimates we find no aggregate net effect of dam construction in the average river basin. The findings also show that dams amplify the negative impact of rainfall shocks both in the river basin where the dam is built and in downstream river basins. However, the negative impact of large rainfall shocks on child height and weight is more exacerbated in the river basin where the dam is located than in downstream river basins. We also document some relevant heterogeneity of the effect of dams along some demographic characteristics. We find that among children living in areas downstream from a dam, girls, children living in male-headed households and whose mothers are more educated benefit more from the dam. In the river basin where the dam is located we find no systematic differences in the effect of dams across demographic groups. Taken together these findings demonstrate that dam construction in Sub-Saharan Africa clearly creates losers and winners showing the scope for more effective policy making in order to capture the benefits from investing in large dam while compensating those who would lose. The remainder of this paper is organized as follows. Section 1.2 discusses the importance of adequate childhood nutrition on later physical and cognitive development. Section 1.3 presents the data. Section 1.4 presents in detail how the unit of analysis was chosen and presents the policy context that motivates the empirical strategy. Section 1.5 outlines the empirical strategy. Section 1.6 presents the results and section 1.7 concludes. In addition, the construction of a dam is likely to affect the nutritional status of children differently depending on whether their family reside in the catchment area of the dam or downstream. Improved access to irrigation increases agricultural productivity in river basins located downstream while in the river basin where the dam is built, water logging and soil salinity are likely to increase. This in turn leads to a reduction in the gross area cultivated and to lower agricultural productivity. As a result access to food and the nutritional status of children are likely to decrease in the river basin where the dam is built but increase in downstream river basins. Trade in food and agricultural inputs between the river basins where the dam is built and downstream river basins may dampen the negative effect of the dam in its catchment area. For instance, in the presence of trade, the increased production downstream from the dam can result in the reduction of the relative price of food and seeds in the river basins where the dam is built and upstream. This will partially counterbalance the direct negative effect of the dam construction on agricultural production and productivity. However given that a large proportion of rural household’s income is derived from the sale of their production households residing in the river basin where the dam is built may have limited purchasing power to benefit from the trade of goods. We use FAO’s African Dams Database, a geo-referenced database of large dams, to geographically locate African dams using exact latitude and longitude of the dams provided by the World Register of Dams, national reports, national experts and the internet. The database only covers the period prior to 2002. According to the ICOLD definition a dam is “large” if it has height of at least 15 meters or, if smaller has a reservoir of at least 3 million m3 . The FAO’s African Dams Database has a total of 1138 geo-referenced dams, for a number of dams information on the latitude and longitude or the completion date was not recorded. We were able to fill the missing information from updated ICOLD data and internet searches, leaving us with 972 dams for our analysis. In this sample about 65 per cent of dams have some irrigation purpose, while for 15% hydropower is a major purpose. We depict the location of the 972 dams in our sample in Figure 1.1. As can be seen, dams are not uniformly distributed across space, with most dams located in the southern, western and north-western parts of the continent. Moreover, many areas with large rivers and lakes do not have any dam. In Figure 1.2 we show the cumulative number of dams built over time across Africa. Since 1950 the number of dams built has substantially risen but has leveled off during the 90’s. Our analysis excludes all dams for which we do not have information on the date of completion. To investigate the risk of bias from this procedure, we report in Table 1.1 the characteristics of those dams when available. The results show that the dams excluded from the sample are more likely to be used for navigation, recreational or pollution control purposes.