Estimating groundwater use and demand in arid Kenya through assimilation of satellite data and in-situ sensors with machine learning toward drought early action.

Groundwater is an important source of water for people, livestock, and agriculture during drought in the Horn of Africa. In this work, areas of high groundwater use and demand in drought-prone Kenya were identified and forecasted prior to the dry season. Estimates of groundwater use were extended from a sentinel network of 69 in-situ sensored mechanical boreholes to the region with satellite data and a machine learning model. The sensors contributed 756 site-month observations from June 2017 to September 2021 for model building and validation at a density of approximately one sensor per 3700 km2. An ensemble of 19 parameterized algorithms was informed by features including satellite-derived precipitation, surface water availability, vegetation indices, hydrologic land surface modeling, and site characteristics to dichotomize high groundwater pump utilization. Three operational definitions of high demand on groundwater infrastructure were considered: 1) mechanical runtime of pumps greater than a quarter of a day (6+ hr) and daily per capita volume extractions indicative of 2) domestic water needs (35+ L), and 3) intermediate needs including livestock (75+ L). Gridded interpolation of localized groundwater use and demand was provided from 2017 to 2020 and forecasted for the 2021 dry season, June-September 2021. Cross-validated skill for contemporary estimates of daily pump runtime and daily volume extraction to meet domestic and intermediate water needs was 68%, 69%, and 75%, respectively. Forecasts were externally validated with an accuracy of at least 56%, 70%, or 72% for each groundwater use definition. The groundwater maps are accessible to stakeholders including the Kenya National Drought Management Authority (NDMA) and the Famine Early Warning Systems Network (FEWS NET). These maps represent the first operational spatially-explicit sub-seasonal to seasonal (S2S) estimates of groundwater use and demand in the literature. Knowledge of historical and forecasted groundwater use is anticipated to improve decision-making and resource allocation for a range of early warning early action applications.

Mixed methods study design, pre-analysis plan, process evaluation and baseline results of trailbridges in rural Rwanda.

We present a study design, pre-analysis plan, process evaluation and baseline results designed to establish the impact of trailbridges on health, education, agricultural and economic outcomes of households in rural Rwanda. This intervention and study is being implemented in communities that face barriers to socioeconomic development through periodic isolation caused by flooding. We describe a mixed methods approach to measure the impacts of these trailbridges on outcomes at the village level. The study is anchored on a stepped-wedge randomized controlled trial (RCT) implemented in 147 sites: 97 phased-in intervention sites and 50 long-term control sites. These sites are being monitored in four annual waves comprising of a baseline period and three subsequent follow-up waves. We will supplement the RCT with three sub-studies. First, we are investigating the role of weather events and streamflow variability on temporal and spatial bridge use patterns among intervention sites. We will then find the relationship between the weather events, streamflow and bridge use from motion-activated cameras installed in intervention sites. Secondly, we are following 42 markets serving study sites to investigate the impact of the trailbridges on the market prices of key goods including crops, livestock and agricultural inputs. Lastly, we are following 30 villages that are more distant from the river crossings to determine the spatial extent of the trailbridge impacts. Our study will advance knowledge by generating new data on the impact of rural infrastructure and providing the opportunity to explore a range of outcomes for future evaluation of infrastructure in low- and middle-income countries. We will enable an outcomes-based funding model that ties implementer payments to demonstrated positive impacts of these trailbridges. Furthermore, we will identify cost-effective, easily assessed measures that are highly correlated to the economic and health benefits of the intervention. These measures may then be used by a portfolio of interventions across multiple geographies without always requiring complex trials.

Quantifying increased groundwater demand from prolonged drought in the East African Rift Valley.

Millions of people in the arid regions of Kenya and Ethiopia face water scarcity and frequent drought. Water resource forecasting and reliable operation of groundwater distribution systems may improve drought resilience. In this study, we examined three remote sensing data sets against in-situ sensor-collected groundwater extraction data from 221 water points serving over 1.34 million people across northern Kenya and Afar, Ethiopia between January 1, 2017 and August 31, 2018. In models containing rainfall as a binary variable, we observed an overall 23% increase in borehole runtime following weeks with no rainfall compared to weeks preceded by some rainfall. Further, a 1 mm increase in rainfall was associated with a 1% decrease in borehole use the following week. When surface water availability is reduced during the dry seasons, groundwater demand increases. Our findings emphasize the imperative to maintain functionality of groundwater boreholes in these regions which often suffer drought related emergencies. Funding provided by the United States Agency for International Development, the World Bank, the National Science Foundation, and the Cisco Foundation. The views expressed in this article do not necessarily reflect the views of the United States Agency for International Development or the United States Government.