## 3 Results
The number of households and livestock being served by each water system was also statistically significant (\(p=0.005\) and \(p=0.0242\)), although the effect size per thousand was small (\(-0.195\) and \(-0.0343\)). However, sites used for filling water trucks were used on average three hours more compared to sites not used for water trucking (\(p<0.001\)), and urban sites were used 3.25 h more than rural sites (\(p<0.001\)). Sites where the operator reported using the water system less during the rainy season averaged slightly more use on average compared to non-seasonal sites (\(0.713,p=0.0278\)). However, in general sites were used 0.383 h less during the rainy season compared to the dry season (\(p=0.0024\)). Similarly, sites that reported using a surface water source when the water system was non-functional were used almost an hour less per day on average compared to sites that reported using a different water tap (\(p=0.0128\)). A surprising finding was that sites designated as strategic boreholes were used almost two hours less on average compared to non-strategic boreholes (\(p=0.0010\)), even when controlling for all the fixed effects listed above. To better understand why strategic boreholes were used less, we constructed two additional models to explore the interactions between borehole status, county activities, and drought conditions. In the first exploratory model (i.e., \(Hours_{it}=\beta_{00}+\beta_{01-04}(County_{i})+\beta_{05}(Borelobe\_Status_{i})+ \beta_{06}(County_{i}*Borelobe\_Status_{i})+U_{0i}+\varepsilon_{it}\)), we found that interactions between borehole status and county were only significant for Isiolo and Wajir. This is further demonstrated in Figure 4, where the average reduction in water system use for strategic boreholes was greater for these two counties. However, it is important to note that borehole statuses were severely unbalanced in Wajir and Isiolo because there was only one non-strategic borehole that was monitored in Wajir and only four strategic boreholes monitored in Isiolo. \begin{table}
\begin{tabular}{l c c} \hline  & **Coefficient (SE)** & \(p\)**-Value** \\ \hline Intercept & 3.95 (0.795) & \(<\)0.001 \\ County: Garissa (reference) & NA & NA \\ County: Isiolo & \(-1.94\) (0.686) & 0.0058 \\ County: Marsabit & 0.514 (0.592) & 0.388 \\ County: Turkana & 2.33 (0.690) & 0.0011 \\ County: Wajir & 2.39 (0.558) & 0.0001 \\ Strategic borehole Status & \(-1.33\) (0.384) & 0.0009 \\ Households Served (1000s) & \(-0.195\) (0.0541) & 0.0005 \\ Livestock Served (1000s) & \(-0.0343\) (0.0149) & 0.0242 \\ Power: Generator (reference) & NA & NA \\ Power: Hybrid & 1.11 (0.375) & 0.0043 \\ Power: Solar & \(-0.959\) (0.516) & 0.0667 \\ Power: Utility & 3.56 (0.666) & \(<\)0.001 \\ Seasonal Pump & 0.685 (0.319) & 0.0349 \\ Alt. Surface Water Source & \(-0.982\) (0.337) & 0.0091 \\ Rainy Season & \(-0.389\) (0.126) & 0.0021 \\ Water Trucking & 3.03 (0.348) & \(<\)0.001 \\ Urban Location & 3.23 (0.578) & \(<\)0.001 \\ \hline \end{tabular}
\end{table} 
Table 2: Multilevel model results for all data. In the second exploratory model (i.e., \(Hours_{it}=\beta_{00}+\beta_{01}(Borelhole\_Status_{i})+U_{0i}+\beta_{10}( Drought\_Period_{it})+\beta_{11}(Borelhole\_Status_{i}* Drought\_Period_{it})+\varepsilon_{it}\)) we looked at differences in water system use when controlling for drought conditions. As noted previously, there was significantly less precipitation in 2017 compared to 2018. One consequence is that the NDMA was more active in each of the counties in 2017, not only assessing drought risk and coordinating execution of each county's contingency action plan, but also providing significant assistance through water trucking, fuel subsidies, water equipment, and support to emergency repair teams. When the 2017 drought began in June, there were only 25 sensors installed on water systems, and only eight of those water systems were designated as strategic boreholes.