In the face of climate change, urban stormwater management practices are subject to an uncertain context. More frequent and extreme rainfall events are expected in many urban areas. The extent how climate change will affect weather patterns is however uncertain. This challenges contemporary stormwater management practices. A post-disaster reconstruction of an urban area would potentially be an opportunity to anticipate climate change uncertainties from the initial design phase of new urban development. This would allow for taking advantage of the disaster recovery by rebuilding a more resilient stormwater system than was present before, in which the uncertainties are anticipated. A resilient stormwater system would thus be able to cope a wide range of plausible futures, rather than the average. As academic literature lacks insight on re-establishing resilient urban stormwater management in a post-disaster reconstruction, this thesis aims to gain more insights into what extent resilient urban stormwater management has been established in a Tsunami reconstruction, with regard to uncertainties on climate change and urban development. A case study is conducted in which is focused on a) the conducted design approach, b) the realm of conditions for which the implemented stormwater system would be vulnerable and c) which solutions could be implemented to reduce the vulnerability, and reflected upon opportunities of an interdisciplinary approach from a stormwater management perspective. The selected study area is a town called Ötsuchi Town, in Northern Japan, Iwate Prefecture, which was severely hit during the 2011 Tsunami. The disaster necessitated a comprehensive reconstruction. To gain more insight into what extent a resilient urban stormwater system has been implemented, an exploratory modelling and analysis approach has been applied, which is also known as Scenario Discovery. Prime drivers of Scenario Discovery are exploring the system's performance for wide-ranging plausible futures by sampling the system myriad times with aid of computational modelling, and, the use of regional sensitivity mapping algorithms to understand the dominant factors that lead to insufficient system performance. The latter can be used as input for seeking vulnerability-reducing strategies. In this research, the Patient Rule Induction Method (PRIM) algorithm is used to understand the conditions for which the stormwater drainage system capacity would be exceeded, for an acceptable flooding level of 0.2 meter. Two open-source tools were combined: the conceptual stormwater flow model EPA-SWMM, and, python library EMA-workbench which provides the tools needed for applying Scenario Discovery and supportive analysis. After the 2011 Tsunami a separate half-open sewer system was established in the reclamation area of Ötsuchi Town. No natural-based solutions, or Blue-Green infrastructure were implemented, even though the residential is adjacent to steep mountain slopes. The uncertainty parameters over which is sampled, include rainfall intensity, rainfall duration, external runoff coefficient, imperviousness, the hydraulic conductivity, Manning's roughness coefficient and depression storage. The Scenario Discovery results show that the system has been built robust. For almost all locations no flooding occurrence arise from the sampling, even for very extreme rainfall events (>100 mm/hr, for a duration of 60 min). However, when the runoff coefficient of the external runoff from the mountain would be above 0.58, a small area in the northern part would be vulnerable. The dominant factors, are found with PRIM and the relative weights are with very high precision and recall found by pre-processing the sampling data with Principal Component Analysis. It showed that for the vulnerable area, the hydraulic conductivity of the soil and the proportion of paved area are decisive in whether or not flooding occurs. Paying attention to certain thresholds, would significantly reduce the vulnerability of flooding occurrence. Given the high volumes for which flooding would occur, a preliminary feasibility study has been done for both a vegetative swale and infiltration trenches, in combination with a storage retention area in the lower lying area, such that the pressure on the stormwater drainage system can be released. The vegetative swale reduce the vulnerability significantly. The infiltration trenches seem to be effective for the lower rainfall duration and rainfall intensity. PCA-PRIM outcome showed that when implementing infiltration trenches in the vulnerable area, the impervious rate becomes relatively less sensitive in comparison with outcomes of PRIM with the reference situation. More information on mountain runoff, soil properties and land use would enhance the accuracy of the results. In addition, since, no information is known yet on initial losses of mountain runoff, more information on runoff flow processes from the mountains would enable to perform joint probability analysis with the results of this research, to better assess whether or not the time is now to implement additional measures. From the results of this research it seems that the urban stormwater drainage of Ötsuchi Town has been rebuilt very robust, however when the system would fail, no additional measures outside the grey infrastructure are taken. An interdisciplinary approach could have encouraged a more resilient stormwater management. As this research shows that multiple commutative reconstruction measures could be found from a stormwater management perspective, the obtained information with applying Scenario Discovery, would have been useful to encourage an interdisciplinary approach during the reconstruction process. It is therefore suggested to explore the usage of Scenario Discovery on urban stormwater management even further, such that it enables to take advantage of the disaster reconstruction to establish a resilient urban stormwater management. An example would be to investigate whether the relative sensitivity of the uncertainty parameters would change when a less robust system would be examined. For example, for an urban drainage system for which the threshold would already be exceeded for lower rainfall intensity and duration than 100 mm/hr, and 60 minutes respectively. In addition, a coarse representation of rainfall events are considered in this research. Therefore it would be suggested to examine the applicability of region-specific storm profiles in combination with an exploratory modelling and analysis approach, to better assess the implication of the PRIM outcomes for implementing resilient urban stormwater management strategies.

IHE-Delft in cooperation with the Asian Development Bank (ADB) conducts a pilot project on assessing Crop Water Productivity in Asia, aiming to contribute to sustainable development in Asia’s irrigation sector, and create more value from scarce water resources. Indonesia is one of the 6 pilot countries where advanced technologies to measure Water Productivity (WP) from satellite data were introduced. Indonesia is the third largest rice producer of the world. Given the challenges such as growing population, degrading land and increasing water scarcity in upcoming decades, the Indonesian government aims to rehabilitate its irrigation systems. More insights in the spatial distribution of irrigation water and water productivity of rice paddies could contribute to decision-making in future rehabilitation investments.
This report describes the assessment of Water Productivity (WP) of paddy rice in Indonesia using the Surface Energy Balance Algorithm for Land (SEBAL). SEBAL is a tool that translates raw satellite measurements into maps of actual evapotranspiration and crop production, among others. The actual crop water consumption (i.e. actual evapotranspiration) and crop yield can now be estimated for every 30 m x 30 m, even if data on irrigation water application is not available. With this information, rice production per unit of land (kg/ha) as well as per unit of water consumed (kg/m3) can be computed.
Focus of this study are sites in Bali, West Java and Lombok. Fieldwork is conducted in Bali and West Java to support the maps with ‘ground truth’ data. Data is collected from local governmental institutes and farmers to verify the remote sensing outputs.
This research shows promising results linking SEBAL outputs with the ground truth even though the amount of fieldwork was limited. The inclusion of the new HANTS algorithm will create the technical opportunity to make daily WP reports for all rice fields in Indonesia, also under cloudy conditions. This could be a big information boost to support irrigation managers with their daily services of bringing water to farmers. Whereas some key explanatory reasons were detected (i.e. distance to canal, salt water intrusion, water quality, erosion), it is recommended to further explore relations between WP and influencing factors in the local context together with local irrigation officers. Even though the research revealed some limitations causing uncertainties, this new remote sensing technologies can support an efficient and effective investment purposes on modernization of irrigation. It is recommended that the Directorate of Irrigation and Lowlands recognize WP as a new policy instrument and implement it both at central level and irrigation district level.