Martine Rutten

Feasibility of soil moisture estimation using passive distributed temperature sensing

Through its role in the energy and water balances at the land surface, soil moisture is a key state variable in surface hydrology and land?atmosphere interactions. Point observations of soil moisture are easy to make using established methods such as time domain reflectometry and gravimetric sampling. However, monitoring large?scale variability with these techniques is logistically and economically infeasible. Here passive soil distributed temperature sensing (DTS) will be introduced as an experimental method of measuring soil moisture on the basis of DTS. Several fiber?optic cables in a vertical profile are used as thermal sensors, measuring propagation of temperature changes due to the diurnal cycle. Current technology allows these cables to be in excess of 10 km in length, and DTS equipment allows measurement of temperatures every 1 m. The passive soil DTS concept is based on the fact that soil moisture influences soil thermal properties. Therefore, observing temperature dynamics can yield information on changes in soil moisture content. Results from this preliminary study demonstrate that passive soil DTS can detect changes in thermal properties. Deriving soil moisture is complicated by the uncertainty and nonuniqueness in the relationship between thermal conductivity and soil moisture. A numerical simulation indicates that the accuracy could be improved if the depth of the cables was known with greater certainty.

Continuity vs. the Crowd—Tradeoffs Between Continuous and Intermittent Citizen Hydrology Streamflow Observations

Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology and local residents to collect hydrologic data at many sites. However, understanding of how decreased observational frequency impacts the accuracy of key streamflow statistics such as minimum flow, maximum flow, and runoff is limited. To evaluate this impact, we randomly selected 50 active United States Geological Survey streamflow gauges in California. We used 7 years of historical 15-min flow data from 2008 to 2014 to develop minimum flow, maximum flow, and runoff values for each gauge. To mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, and their respective distributions, from 50 subsample iterations with four different subsampling frequencies ranging from daily to monthly. Minimum flows were estimated within 10% for half of the subsample iterations at 39 (daily) and 23 (monthly) of the 50 sites. However, maximum flows were estimated within 10% at only 7 (daily) and 0 (monthly) sites. Runoff volumes were estimated within 10% for half of the iterations at 44 (daily) and 12 (monthly) sites. Watershed flashiness most strongly impacted accuracy of minimum flow, maximum flow, and runoff estimates from subsampled data. Depending on the questions being asked, lower frequency Citizen Hydrology observations can provide useful hydrologic information.

Determining water reservoir characteristics with global elevation data

Quantification of human impact on water, sediment, and nutrient fluxes at the global scale demands characterization of reservoirs with an accuracy that is presently unavailable. This letter presents a new method, based on virtual dam placement, to make accurate estimations of area-volume relationships of large reservoirs, using solely readily available elevation data. The new method is based on regional similarity of area-volume relationships. The essence of the method is that virtual reservoirs are created in the vicinity of an existing reservoir to derive area-volume relationships for the existing reservoir. The derived area-volume relationships reproduced in situ bathymetric data well. An intercomparison for twelve reservoirs resulted in an average R2 = 0.93. This is a significant improvement on estimates using the best existing global regression model, which gives R2 = 0.54 for the same set of reservoirs.

Quantifying the connections—linkages between land-use and water in the Kathmandu Valley, Nepal

Land development without thoughtful water supply planning can lead to unsustainability. In practice, management of our lands and waters is often unintegrated. We present new land-use, ecological stream health, water quality, and streamflow data from nine perennial watersheds in the Kathmandu Valley, Nepal, in the 2016 monsoon (i.e., August and September) and 2017 pre-monsoon (i.e., April and May) periods. Our goal was to improve understanding of the longitudinal linkages between land-use and water. At a total of 38 locations, the Rapid Stream Assessment (RSA) protocol was used to characterize stream ecology, basic water quality parameters were collected with a handheld WTW multi-parameter meter, and stream flow was measured with a SonTek FlowTracker Acoustic Doppler Velocimeter. A pixel-based supervised classification method was used to create a 30-m gridded land use coverage from a Landsat 8 image scene captured in the fall of 2015. Our results indicated that land-use had a statistically significant impact on water quality, with built land-uses (high and low) having the greatest influence. Upstream locations of six of the nine watersheds investigated had near natural status (i.e., river quality class (RQC) 1) and water could be used for all purposes (after standard treatments as required). However, downstream RSA measurements for all nine watersheds had RQC 5 (i.e., most highly impaired). Generally, water quality deteriorated from monsoon 2016 to pre-monsoon 2017. Our findings reinforce the importance of integrated land and water management and highlight the urgency of addressing waste management issues in the Kathmandu Valley.

Offset-Free Model Predictive Control of an Open Water Channel Based on Moving Horizon Estimation

AbstractOpen water systems such as irrigation canals are used to transport and deliver water from the source to the user. Water loss in these systems by seepage, leakage, evaporation, or unknown water offtakes can be large. If this loss is unknown to the model used, it will not be considered by the controller and create a real system model mismatch. This mismatch will affect the water level directly and create an offset from the reference set point of the water level. A control configuration for open water canals, model predictive control (MPC) based on moving horizon estimation (MHE-MPC), to deal with offset problems resulting from real system-model mismatch is described in this paper. MHE uses the past predictions of the model and the past measurements of the system to estimate unknown disturbances and systematically removes the offset in the controlled water level. This control configuration is numerically tested on an accurate hydrodynamic model of the Control Algorithms Test Canal of the Technical Un...

Acceptance of Mobile Technology for Citizen Science in Water Resource Management

AbstractDutch water management is considered highly efficient, but it faces a lack of public awareness and other certain physical challenges. One proposed strategy to deal with these challenges includes increasing citizen participation and citizen science using mobile devices in particular. Such mobile crowd sensing (MCS) can be used to enhance canal operations and model predictive control (MPC) by nonexperts. The data collector often pushes implementations, and little knowledge and experience from the field of product design is used. This can lead to underperformance both with regards to the technology and the volunteer citizens. This study uses an adapted Technology Acceptance Model 3 (TAM3) to survey Dutch citizens’ intentions while operating a mock-up smartphone application to identify key drivers of their acceptance in an early design phase. Included among the important drivers of citizens’ behavioral intentions (BI) are usefulness, relevance to the task, and the demonstrability of benefits. These in...