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1. Assessing the impacts of anthropogenic drainage structures on hydrologic connectivity using high‐resolution digital elevation models

   https://doi.org/10.1111/tgis.12832  

   Bhadra, Sourav; Li, Ruopu; Wu, Di; Wang, Guangxing; Rekabdar, Banafsheh (August 2021, Transactions in GIS)

   Abstract Delineating accurate flowlines using digital elevation models is a critical step for overland flow modeling. However, extracting surface flowlines from high‐resolution digital elevation models (HRDEMs) can be biased, partly due to the absence of information on the locations of anthropogenic drainage structures (ADS) such as bridges and culverts. Without the ADS, the roads may act as “digital dams” that prevent accurate delineation of flowlines. However, it is unclear what variables for terrain‐based hydrologic modeling can be used to mitigate the effect of “digital dams.” This study assessed the impacts of ADS locations, spatial resolution, depression processing methods, and flow direction algorithms on hydrologic connectivity in an agrarian landscape of Nebraska. The assessment was conducted based on the offset distances between modeled drainage crossings and actual ADS on the road. Results suggested that: (a) stream burning in combination with the D8 or D‐Infinity flow direction algorithm is the best option for modeling surface flowlines from HRDEMs in an agrarian landscape; (b) increasing the HRDEM resolution was found significant for facilitating accurate drainage crossing near ADS locations; and (c) D8 and D‐Infinity flow direction algorithms resulted in similar patterns of drainage crossing at ADS locations. This research is expected to result in improved parameter settings for HRDEMs‐based hydrologic modeling. 

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2. Riverscape genomics of cichlid fishes in the lower Congo: Uncovering mechanisms of diversification in an extreme hydrological regime

   https://doi.org/DOI: 10.1111/mec.16495  

   Naoko, P. Kurata; Michael, J. Hickerson; Sandra, L. Hoffberg; Ned, Gardiner; Melanie, L. J.; S. Elizabeth, Alter (May 2022, Molecular ecology)

   Freshwater fishes are notably diverse, given that freshwater habitat represents a tiny fraction of the earth's surface, but the mechanisms generating this diversity remain poorly understood. Rivers provide excellent models to understand how freshwater diversity is generated and maintained across heterogeneous habitats. In particular, the lower Congo River (LCR) consists of a dynamic hydroscape exhibiting extraordinary aquatic biodiversity, endemicity, morphological and ecological specialization. Previous studies have suggested that the numerous high-energy rapids throughout the LCR form physical barriers to gene flow, thus facilitating diversification and speciation, generating ichthyofaunal diversity. However, this hypothesis has not been fully explored using genome-wide SNPs for fish species distributed across the LCR. Here, we examined four lamprologine cichlids endemic to the LCR that are distributed along the river without range overlap. Using genome-wide SNP data, we tested the hypotheses that high-energy rapids serve as physical barriers to gene flow that generate genetic divergence at interspecific and intraspecific levels, and that gene flow occurs primarily in a downstream direction. Our results are consistent with the prediction that powerful rapids sometimes act as a barrier to gene flow but also suggest that, at certain temporal and spatial scales, they may provide multidirectional dispersal opportunities for riverine rheophilic cichlid fishes. These results highlight the complexity of diversification processes in rivers and the importance of assessing such processes across different riverscapes. 

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3. Distinguishing Time Scales of Katabatic Flow in Complex Terrain

   https://doi.org/10.3390/atmos12121651  

   Drake, Stephen; Higgins, Chad; Pardyjak, Eric (December 2021, Atmosphere)

   To examine spatial and temporal scales of katabatic flow, a distributed temperature sensing (DTS) optical fiber was deployed 2 km down a mild slope irregularly interrupted by small-scale drainage features as part of the Mountain Terrain Atmospheric Modeling and Observation (MATERHORN) experiment conducted at the U.S. Army Dugway Proving Ground, Utah. The fiber was suspended at two heights near the surface, enabling measurement of variations in lapse rate near the surface at meter-scale spatial resolution with 1-min temporal resolution. Experimental results derived from the DTS and tower-mounted instrumentation indicate that airflow through small-scale drainage features regulated the local cooling rate whereas topographic slope and distance along the drainage strongly influenced the larger-scale cooling rate. Empirical results indicate that local cooling rate decays exponentially after local sunset and basin-wide cooling rate decreases linearly with time. The difference in the functional form for cooling rate between local and basin-wide scales suggests that small-scale features have faster timescales that manifests most strongly shortly after local sunset. More generally, partitioning drainage flow by scale provides insight and a methodology for improved understanding of drainage flow in complex terrain. 

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4. Spatially Explicit Fuzzy Cognitive Mapping for Participatory Modeling of Stormwater Management

   https://doi.org/10.3390/land10111114  

   White, Corey T.; Mitasova, Helena; BenDor, Todd K.; Foy, Kevin; Pala, Okan; Vukomanovic, Jelena; Meentemeyer, Ross K. (November 2021, Land)

   Addressing “wicked” problems like urban stormwater management necessitates building shared understanding among diverse stakeholders with the influence to enact solutions cooperatively. Fuzzy cognitive maps (FCMs) are participatory modeling tools that enable diverse stakeholders to articulate the components of a socio-environmental system (SES) and describe their interactions. However, the spatial scale of an FCM is rarely explicitly considered, despite the influence of spatial scale on SES. We developed a technique to couple FCMs with spatially explicit survey data to connect stakeholder conceptualization of urban stormwater management at a regional scale with specific stormwater problems they identified. We used geospatial data and flooding simulation models to quantitatively evaluate stakeholders’ descriptions of location-specific problems. We found that stakeholders used a wide variety of language to describe variables in their FCMs and that government and academic stakeholders used significantly different suites of variables. We also found that regional FCM did not downscale well to concerns at finer spatial scales; variables and causal relationships important at location-specific scales were often different or missing from the regional FCM. This study demonstrates the spatial framing of stormwater problems influences the perceived range of possible problems, barriers, and solutions through spatial cognitive filtering of the system’s boundaries. 

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5. Effect of Watershed Delineation and Climate Datasets Density on Runoff Predictions for the Upper Mississippi River Basin Using SWAT within HAWQS

   https://doi.org/10.3390/w13040422  

   Chen, Manyu; Cui, Yuanlai; Gassman, Philip; Srinivasan, Raghavan (February 2021, Water)

   null (Ed.)

   The quality of input data and the process of watershed delineation can affect the accuracy of runoff predictions in watershed modeling. The Upper Mississippi River Basin was selected to evaluate the effects of subbasin and/or hydrologic response unit (HRU) delineations and the density of climate dataset on the simulated streamflow and water balance components using the Hydrologic and Water Quality System (HAWQS) platform. Five scenarios were examined with the same parameter set, including 8- and 12-digit hydrologic unit codes, two levels of HRU thresholds and two climate data densities. Results showed that statistic evaluations of monthly streamflow from 1983 to 2005 were satisfactory at some gauge sites but were relatively worse at others when shifting from 8-digit to 12-digit subbasins, revealing that the hydrologic response to delineation schemes can vary across a large basin. Average channel slope and drainage density increased significantly from 8-digit to 12-digit subbasins. This resulted in higher lateral flow and groundwater flow estimates, especially for the lateral flow. Moreover, a finer HRU delineation tends to generate more runoff because it captures a refined level of watershed spatial variability. The analysis of climate datasets revealed that denser climate data produced higher predicted runoff, especially for summer months. 

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