A socio-hydrologic framework for understanding conflict and cooperation in transboundary rivers

Increasing hydrologic variability, accelerating population growth, and resurgence of water resources development projects have all indicated increasing tensions among the riparian countries of transboundary rivers. This article aims to review the existing knowledge on conflict and cooperation in transboundary rivers from a multidisciplinary perspective and propose a socio-hydrological framework that integrates the slow and less visible societal processes with existing hydrological-economic models, revealing the hidden feedbacks between changes in societal processes and hydrological changes. This framework contributes to understanding the mechanism that drives conflict and cooperation in transboundary river management.

Location, location, location -- Considering relative catchment location to understand subsurface losses

The analysis of large samples of hydrologic catchments is regularly used to gain understanding of hydrologic variability and controlling processes. Several studies have pointed towards the problem that available catchment descriptors (such as mean topographic slope or average subsurface properties) are insufficient to capture hydrologically relevant properties. Here, we test the assumption that catchment location, i.e. the relative properties of catchments in relation to their surrounding neighbours, can provide additional information to reduce this problem. We test this idea in the context of Great Britain for a widely discussed problem, that of catchment water balance errors due to subsurface losses. We test three hypotheses while considering different locational aspects (1) location to coast, (2) location next a relevant neighbour and (3) location within the drainage basin, utilizing only basic and widely available geological and topographical information. We find that subsurface losses from catchments with a highly permeable geology connection to the coast are in order of 20% water balance error. We define a simple topographic-geologic index that is able to partially explain water balance issues between neighbours of highly permeable catchments. The results imply that location, geology and topography combine to define the differences of water balances of UK catchments compared to what we would expect from their climatic setting alone. The simple index defined here can easily be derived globally and tested regarding its wider applicability.

A comparison of western Great Basin paleoclimate records for the last 3000 yr: Evidence for multidecadal- to millennial-scale drought

ABSTRACT This paper summarizes the hydrological variability in eastern California (central Sierra Nevada) for the past 3000 yr based on three distinct paleoclimate proxies, δ18O, total inorganic carbon (TIC), and magnetic susceptibility (chi). These proxies, which are recorded in lake sediments of Pyramid Lake and Walker Lake, Nevada, and Mono Lake and Owens Lake, California, indicate lake-level changes that are mostly due to variations in Sierra Nevada snowpack and rainfall. We evaluated lake-level changes in the four Great Basin lake systems with regard to sediment-core locations and lake-basin morphologies, to the extent that these two factors influence the paleoclimate proxy records. We documented the strengths and weaknesses of each proxy and argue that a systematic study of all three proxies together significantly enhances our ability to characterize the regional pattern, chronology, and resolution of hydrological variability. We used paleomagnetic secular variation (PSV) to develop paleomagnetic chronostratigraphies for all four lakes. We previously published PSV records for three of the lakes (Mono, Owens, Pyramid) and developed a new PSV record herein for Walker Lake. We show that our PSV chronostratigraphies are almost identical to previously established radiocarbon-based chronologies, but that there are differences of 20–200 yr in individual age records. In addition, we used eight of the PSV inclination features to provide isochrons that permit exacting correlations between lake records. We also evaluated the temporal resolution of our proxies. Most can document decadal-scale variability over the past 1000 yr, multidecadal-scale variability for the past 2000 yr, and centennial-scale variability between 2000 and 3000 yr ago. Comparisons among our proxies show a strong coherence in the pattern of lake-level variability for all four lakes. Pyramid Lake and Walker Lake have the longest and highest-resolution records. The δ18O and TIC records yield the same pattern of lake-level variability; however, TIC may allow a somewhat higher-frequency resolution. It is not clear, however, which proxy best estimates the absolute amplitude of lake-level variability. Chi is the only available proxy that records lake-level variability in all four lakes prior to 2000 yr ago, and it shows consistent evidence of a large multicentennial period of drought. TIC, chi, and δ18O are integrative proxies in that they display the cumulative record of hydrologic variability in each lake basin. Tree-ring estimations of hydrological variability, by contrast, are incremental proxies that estimate annual variability. We compared our integrated proxies with tree-ring incremental proxies and found a strong correspondence among the two groups of proxies if the tree-ring proxies are smoothed to decadal or multidecadal averages. Together, these results indicate a common pattern of wet/dry variability in California (Sierra Nevada snowpack/rainfall) extending from a few years (notable only in the tree-ring data) to perhaps 1000 yr. Notable hydrologic variability has occurred at all time scales and should continue into the future.

Water sharing policies conditioned on hydrologic variability to inform reservoir operations

Water resources infrastructure is critical for energy and food security; however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies for mitigating conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. A water sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions, is proposed. First, the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules is established. Next, reservoir operation with the candidate (optimal) rules is simulated, followed by their performance evaluations, and the rule selections for balancing water uses. Subsequently, a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions is built to derive water sharing policies. Finally, the reservoir operating rules are re-optimized to evaluate the effectiveness of the drought-specific water sharing policies. With a case study of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile river, it is demonstrated that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of water resources.

Streamflow simulation in data-scarce basins using Bayesian and physics-informed machine learning models

Hydrologic predictions at rural watersheds are important but also challenging due to data shortage. Long Short-TermMemory (LSTM) networks are a promising machine learning approach and have demonstrated good performance in streamflow predictions. However, due to its data-hungry nature, most of LSTM applications focused on well-monitored catchments with abundant and high quality observations. In this work, we investigate predictive capabilities of LSTM in poorly monitored watersheds with short observation records. To address three main challenges of LSTM applications in data-scarce locations, i.e., overfitting, uncertainty quantification (UQ), and out-of-distribution prediction, we evaluate different regularization techniques to prevent overfitting, apply a Bayesian LSTM for UQ, and introduce a physics-informed hybrid LSTM to enhance out-of-distribution prediction. Through case studies in two diverse sets of catchments with and without snow influence, we demonstrate that: (1) when hydrologic variability in the prediction period is similar to the calibration period, LSTM models can reasonably predict daily streamflow with Nash-Sutcliffe efficiency above 0.8, even with only two years of calibration data. (2) When the hydrologic variability in the prediction and calibration periods is dramatically different, LSTM alone does not predict well, but the hybrid model can improve the out-of-distribution prediction with acceptable generalization accuracy. (3) L2 norm penalty and dropout can mitigate overfitting, and Bayesian and hybrid LSTM have no overfitting. (4) Bayesian LSTM provides useful uncertainty information to improve prediction understanding and credibility. These insights have vital implications for streamflow simulation in watersheds where data quality and availability are a critical issue.

Transboundary water sharing policies conditioned on hydrologic variability to inform reservoir operations

Water resources infrastructure is critical for energy and food security, however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes, especially in transboundary river basins. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies to mitigate conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. We propose a water-sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions. We first establish the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules. Next, we simulate reservoir operation with the candidate (optimal) rules, evaluate their performance, and select the most suitable rules for balancing water uses. Subsequently, we build a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions to derive water-sharing policies. Finally, we re-optimize the reservoir operating rules to evaluate the effectiveness of the drought-specific water sharing policies. We apply the framework to reservoir operation of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile River. We find that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of transboundary water resources.