Similarity-based approaches in hydrogeology: proposal of a new concept for data-scarce groundwater resource characterization and prediction

A new concept is proposed for describing, analysing and predicting the dynamic behaviour of groundwater resources based on classification and similarity. The concept makes use of the ideas put forward by the “PUB” (predictions in ungauged basins) initiative in surface-water hydrology. One of the approaches developed in PUB uses the principle that similar catchments, exposed to similar weather conditions, will generate a similar discharge response at the catchment outlet. This way, models developed for well-observed catchments can be used to make predictions for ungauged catchments with similar properties (topography, land use, etc.). The concept proposed here applies the same idea to groundwater systems, with the goal to make predictions of the dynamic behaviour of groundwater in poorly observed systems using similarities to well-observed and understood systems. This paper gives an overview of the main ideas, the methodological background, the progress so far, and the challenges that the authors regard as most crucial for further development. One of the main goals of this article is thus to raise interest for this new concept within the groundwater community. There are a multitude of highly interesting aspects to investigate, and a community effort, as with PUB, is required. A second goal is to foster and exchange ideas between the groundwater and surface water research communities who, while often working on similar problems, have often missed the opportunity to learn from each other.

Terrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolution

Models of landscape evolution provide insight into the geomorphic history of specific field areas, create testable predictions of landform development, demonstrate the consequences of current geomorphic process theory, and spark imagination through hypothetical scenarios. While the last 4 decades have brought the proliferation of many alternative formulations for the redistribution of mass by Earth surface processes, relatively few studies have systematically compared and tested these alternative equations. We present a new Python package, terrainbento 1.0, that enables multi-model comparison, sensitivity analysis, and calibration of Earth surface process models. Terrainbento provides a set of 28 model programs that implement alternative transport laws related to four process elements: hillslope processes, surface-water hydrology, erosion by flowing water, and material properties. The 28 model programs are a systematic subset of the 2048 possible numerical models associated with 11 binary choices. Each binary choice is related to one of these four elements – for example, the use of linear or nonlinear hillslope diffusion. Terrainbento is an extensible framework: base classes that treat the elements common to all numerical models (such as input/output and boundary conditions) make it possible to create a new numerical model without reinventing these common methods. Terrainbento is built on top of the Landlab framework such that new Landlab components directly support the creation of new terrainbento model programs. Terrainbento is fully documented, has 100 % unit test coverage including numerical comparison with analytical solutions for process models, and continuous integration testing. We support future users and developers with introductory Jupyter notebooks and a template for creating new terrainbento model programs. In this paper, we describe the package structure, process theory, and software implementation of terrainbento. Finally, we illustrate the utility of terrainbento with a benchmark example highlighting the differences in steady-state topography between five different numerical models.

Inundation Patterns of Farmed Pothole Depressions with Varying Subsurface Drainage

HighlightsFarmed pothole depressions in the Des Moines Lobe were observed to fill due to runoff and shallow subsurface flow.Six of the eight observed potholes flooded for five or more days some time during the two years of observation.Subsurface drainage and surface inlets reduced but did not prevent yield-limiting flooding in the observed potholes. Abstract. The prairie pothole region (PPR) ranges from central Iowa to the northwest into Montana and south central Canada, totaling around 700,000 km2. This area contains millions of potholes, or enclosed topographical depressions, which often inundate with rainfall. Many are located in areas that have been converted to arable agricultural land through installation of artificial drainage. However, even with drainage, potholes will pond or have saturated soil conditions during and after significant rain events. The portion of the PPR that extends into Iowa is known as the Des Moines Lobe. In this two-year study, surface water depth data were collected hourly from eight prairie potholes in the Des Moines Lobe in central Iowa to determine the surface water hydrology. These potholes included surface and subsurface drained row crops and undrained retired land, allowing for drainage comparisons. Inundation lasted five or more days at least once at six of the eight potholes, including four potholes with surface inlets and subsurface drainage, which resulted in four of fourteen growing seasons not producing a yield in part of the pothole. Water balances of four different drainage intensities showed increased infiltration due to subsurface drainage and up to 78% of outflow due to surface inlet drainage. Overall, drainage decreased the number of average inundation days, but heavy precipitation events still caused lengthy inundation periods that resulted in crop loss. Keywords: Farmed wetlands, Prairie pothole, Tile drainage, Water balance.

terrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolution

Models of landscape evolution provide insight into the development of specific field areas, create testable predictions of landform development, demonstrate the consequences of current geomorphic process theory, and spark imagination through hypothetical scenarios. While the last four decades have brought the proliferation of many alternative formulations for the redistribution of mass by Earth surface processes, relatively few studies have systematically compared and tested these alternative equations. We present a new Python modeling package, terrainbento 1.0, that enables multi-model comparison, sensitivity analysis, and calibration of Earth surface process models. terrainbento provides a set of 28 model programs that implement alternative transport laws related to four model elements: hillslope processes, surface-water hydrology, erosion by flowing water, and material properties. The 28 model programs stem from 13 binary choices related to one of these four elements – for example, the use of linear or non-linear hillslope diffusion. terrainbento is an extensible framework: model base classes that treat the elements common to all models (such as input/output and boundary conditions) make it possible to create a new model without re-inventing these common methods. terrainbento is built on top of the Landlab framework, such that new Landlab components directly support the creation of new terrainbento models. terrainbento is fully documented, has 100 % unit test coverage including numerical comparison with % all available analytical solutions for process models, and continuous integration testing. We support future users and developers with introductory Jupyter notebooks and a template for creating new terrainbento model programs. In this paper, we describe the package structure, process model theory, and software implementation of terrainbento. Finally, we illustrate the utility of terrainbento with a benchmark example highlighting the differences in steady state topography between five different process models.

Will the Illinois chorus frog (Pseudacris streckeri illinoensis) survive in Arkansas? A case study of a secretive species In need of protection

The range of the Illinois chorus frog (Pseudacris streckeri illinoensis) in Arkansas is restricted to the eastern quarter of Clay County. Nearly 100% of this species’ native sand-prairie habitat has been converted to agricultural fields. The original range of the Illinois chorus frog encompassed at least 9,982 ha. Although two new localities were identified in 2002, the current range is only 4,399 ha in 2002. This represents a 56% range contraction since 1992. Calling was heard in only 44.5% of its original range. This species may be experiencing a severe range contraction. Decay models predict the extirpation of the Illinois chorus frog in Arkansas within 17.5 to 101 yr. Suggested factors contributing to this range contraction may include drought, pesticide use, changes in surface water hydrology, U.S. E.P.A. Best management practices, and this species’ limited ability to recolonize extirpated sites.