Zeinab Takbiri

The change of nature and the nature of change in agricultural landscapes: Hydrologic regime shifts modulate ecological transitions

Hydrology in many agricultural landscapes around the world is changing in unprecedented ways due to the development of extensive surface and subsurface drainage systems that optimize productivity. This plumbing of the landscape alters water pathways, timings, and storage, creating new regimes of hydrologic response and driving a chain of environmental changes in sediment dynamics, nutrient cycling, and river ecology. In this work we non-parametrically quantify the nature of hydrologic change in the Minnesota River Basin, an intensively managed agricultural landscape, and study how this change might modulate ecological transitions. During the growing season when climate effects are shown to be minimal, daily streamflow hydrographs exhibit sharper rising limbs and stronger dependence on the previous-day precipitation. We also find a changed storage-discharge relationship and show that the artificial landscape connectivity has most drastically affected the rainfall-runoff relationship at intermediate quantiles. Considering the whole year, we show that the combined climate and land-use change effects reduce the inherent nonlinearity in the dynamics of daily streamflow, perhaps reflecting a more linearized engineered hydrologic system. Using a simplified dynamic interaction model that couples hydrology to river ecology, we demonstrate how the observed hydrologic change and/or the discharge-driven sediment generation dynamics may have modulated a regime shift in river ecology, namely extirpation of native mussel populations. We posit that such non-parametric analyses and reduced complexity modeling can provide more insight than highly parameterized models and can guide development of vulnerability assessments and integrated watershed management frameworks. This article is protected by copyright. All rights reserved.

Comment on “Climate and agricultural land use change impacts on streamflow in the upper midwestern United States” by Satish C. Gupta et al.

The paper “Climate and agricultural land use change impacts on streamflow in the upper midwestern United States” by Satish C. Gupta, Andrew C. Kessler, Melinda K. Brown, and Francis Zvomuya (hereafter referred to as Gupta et al.) purports to evaluate “the relative importance of changes in precipitation and LULC (land use, land cover) on streamflow in 29 Hydrologic Unit Code 008 watersheds in the Upper Midwestern United States.” However, as we report here, the approach used by Gupta et al. is wholly inadequate for making such an evaluation. Gupta et al. use strong language to criticize other studies and imply a level of certainty that goes well beyond, and in some cases is entirely unsupported by, the results they have presented. We take this opportunity to point out several critical flaws in their study. This article is protected by copyright. All rights reserved.

Human amplified changes in precipitation-runoff patterns in large river basins of the Midwestern United States

Complete transformations of land cover from prairie, wetlands, and hardwood forests to homogenous row crop agriculture scattered with urban centers are thought to have caused profound changes in hydrology in the Upper Midwestern US since the 1800s. Continued intensification of land use and drainage practices combined with increased precipitation have 10 caused many Midwest watersheds to exhibit higher streamflows today than in the historical past. While changes in crop type and farming practices have been well documented over the past few decades, changes in artificial surface (ditch) and subsurface (tile) drainage systems have not. This makes it difficult to quantitatively disentangle the effects of climate change and artificial drainage intensification on the observed hydrologic change, often spurring controversial interpretations with significant implications for management actions. In this study, we investigate four large (23,000-69,000 km) Midwest river 15 basins that span climate and land use gradients to understand how climate and agricultural drainage have influenced basin hydrology over the last 79 years. We use daily, monthly, and annual flow metrics to document streamflow changes and discuss those changes in the context of climate and land use change. While we detect similar timing of precipitation and streamflow changes in each basin, overall the magnitude and significance of precipitation changes are much less than we detect for streamflows. Of the basins containing greater than 20% area drained by tile and ditches, we observe 2 to 4 fold 20 increases in low flows and 1.5 to 3 fold increases in high and extreme flows. Monthly precipitation has increased slightly for some months in each basin, mostly in fall and winter months (August – March), but total monthly streamflow has increased in all months for the Minnesota River Basin (MRB), every month but April for the Red River Basin (RRB), SeptemberDecember and March in the Illinois River Basin (IRB), and no months in the Chippewa River basin (CRB). Using a water budget, we determined that the soil moisture/groundwater storage term for the intensively drained and cultivated MRB, IRB, 25 and RRB, has decreased by about 200%, 100%, and 30%, respectively while increased by roughly 30% in the largely forested CRB since 1975. We argue that agricultural land use change, through wetland removal and artificial drainage installation, has decreased watershed storage and amplified the streamflow response to precipitation increases in the Midwest. Highly managed basins with large reservoirs and urban centers, such as the Illinois River basin (IRB), may be able to buffer some of these impacts better than largely unregulated systems such as the Minnesota River (MRB) and Red River 30 Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-571, 2016 Manuscript under review for journal Hydrol. Earth Syst. Sci. Published: 11 November 2016 c

Multi-Objective Optimization of Fusegates System under Hydrologic Uncertainties

Fusegates are independent units held only by the gravity installed on the free spillway of existing dams in order to increase reservoir storage and/or discharge capacity. Increasing reservoir storage in many dams can partly sacrifice dam’s reliabilities. So considering the failure risk of a dam together with the amount of increase in the reservoir capacity can prevent selecting fusegates which seriously endanger a dam safety. However, Lack of accurate information on various damage functions and difficulty in quantifying failure consequences are among principal limitations that hinder practical application of conventional approaches which account failure risk in real world hydrosystems problems. This study develops two effective multi-objective frameworks to optimize fusegates’ configuration in order to eliminate the need for such hard-to-get mathematical damage functions and provide valuable information on the failure risk, total cost, and increased water volume of a reservoir. The proposed models find trade-off solutions between two sets of conflicting objectives. The first competing objectives is investment cost and water storage and the second conflicting goals are water storage and failure probability under the inherent and parameter hydrologic uncertainties. Complicated flood routing phenomenon within a reservoir equipped with fusegates is explicitly taken into account to attain a more cost-effective and reliable design without jeopardizing the dam safety. Applicability and performance of the developed optimization schemes are discussed and demonstrated on a real life case study. The multi-objective optimization results represented as an ensemble of diverse trade-off solutions provide decision makers with more insight and understanding of system behavior and different design alternatives.

Optimal Design and Operation of Fuse-Gates Considering Water Loss Due to Gates Tilting

Installation of fuse-gates on free spillways might be a safe and reasonably simple solution to increase reservoir capacity compared with the expensive alternative of dam heightening. This research aims at optimum design of fusegates considering the flood routing process in the reservoir. Owing to the fairly complicated performance of fusegates in flooding condition, its optimum tilting control is a challenging task. The overall expected cost which includes expected cost of water loss and gates replacement as well as the initial gates installation cost is considered as the objective function of the optimization problem. Moreover, an efficient mixed Genetic Algorithm model is utilized to minimize the overall cost. Type of gates, their height and first tilting head are explicitly treated as decision variables. A case example is used to assess the applicability of the proposed optimization scheme. The results indicate that consideration of flood routing could have a significant effect on the optimum design of gates.

A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

Abstract. We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products.