Amaury Tilmant

Impact of the Syrian refugee crisis on land use and transboundary freshwater resources

Significance The notion that sudden impacts on shared international waters can be detected and quantified, even in a war zone, is important to scientists and policy makers, who have been stifled in the past by inaccessibility to such regions and the consequent inability to collect relevant data. Our study uses satellite imagery of war-torn Syria, showing how conflict and migration caused sudden reductions in Syrian agricultural land use and water use. An unexpected effect of the conflict was increased flow in the Yarmouk River to Jordan, which nonetheless remains one of the world’s most water-poor nations. The study illustrates that conflict and human displacement can significantly alter a basin’s water balance with dramatic effects on the transboundary partitioning of water resources. Since 2013, hundreds of thousands of refugees have migrated southward to Jordan to escape the Syrian civil war that began in mid-2011. Evaluating impacts of conflict and migration on land use and transboundary water resources in an active war zone remains a challenge. However, spatial and statistical analyses of satellite imagery for the recent period of Syrian refugee mass migration provide evidence of rapid changes in land use, water use, and water management in the Yarmouk–Jordan river watershed shared by Syria, Jordan, and Israel. Conflict and consequent migration caused ∼50% decreases in both irrigated agriculture in Syria and retention of winter rainfall in Syrian dams, which gave rise to unexpected additional stream flow to downstream Jordan during the refugee migration period. Comparing premigration and postmigration periods, Syrian abandonment of irrigated agriculture accounts for half of the stream flow increase, with the other half attributable to recovery from a severe drought. Despite this increase, the Yarmouk River flow into Jordan is still substantially below the volume that was expected by Jordan under the 1953, 1987, and 2001 bilateral agreements with Syria.

Using stochastic dual dynamic programming in problems with multiple near‐optimal solutions

Stochastic dual dynamic programming (SDDP) is one of the few algorithmic solutions available to optimize large-scale water resources systems while explicitly considering uncertainty. This paper explores the consequences of, and proposes a solution to, the existence of multiple near-optimal solutions (MNOS) when using SDDP for mid or long-term river basin management. These issues arise when the optimization problem cannot be properly parametrized due to poorly defined and/or unavailable data sets. This work shows that when MNOS exists, (1) SDDP explores more than one solution trajectory in the same run, suggesting different decisions in distinct simulation years even for the same point in the state-space, and (2) SDDP is shown to be very sensitive to even minimal variations of the problem setting, e.g., initial conditions—we call this “algorithmic chaos.” Results that exhibit such sensitivity are difficult to interpret. This work proposes a reoptimization method, which simulates system decisions by periodically applying cuts from one given year from the SDDP run. Simulation results obtained through this reoptimization approach are steady state solutions, meaning that their probability distributions are stable from year to year.

A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation

The estimation of spatially-variable actual evapotranspiration (AET) is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE), to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges). Compared to traditional triangle methods, TAVE introduces three unique features: (i) the discretization of the domain as overlapping elevation zones; (ii) a variable wet edge that is a function of elevation zone; and (iii) variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability) along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA) and a global AET product (MOD16) over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%), in contrast to substantial overestimation by TA (+234%) and underestimation by MOD16 (−50%). In forested (non-irrigated, water consuming) regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

A dynamic water accounting framework based on marginal resource opportunity cost

Many river basins throughout the world are increasingly under pressure as water demands keep rising due to population growth, industrialization, urbanization and rising living standards. In the past, the typical answer to meet those demands focused on the supply side and involved the construction of hydraulic infrastructures to capture more water from surface water bodies and from aquifers. As river basins have become more and more developed, downstream water users and ecosystems have become increasingly dependent on the management actions taken by upstream users. The increased interconnectedness between water users, aquatic ecosystems and the built environment is further compounded by climate change and its impact on the water cycle. Those pressures mean that it has become increasingly important to measure and account for changes in water fluxes and their corresponding economic value as they progress throughout the river system. Such basin water accounting should provide policy makers with important information regarding the relative contribution of each water user, infrastructure and management decision to the overall economic value of the river basin. This paper presents a dynamic water accounting approach whereby the entire river basin is considered as a value chain with multiple services including production and storage. Water users and reservoir operators are considered as economic agents who can exchange water with their hydraulic neighbors at a price corresponding to the marginal value of water. Effective water accounting is made possible by keeping track of all water fluxes and their corresponding hypothetical transactions using the results of a hydro-economic model. The proposed approach is illustrated with the Eastern Nile River basin in Africa.

Monitoring small reservoirs storage from satellite remote sensing in inaccessible areas

In river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not measured or not readily available due to financial, political, or legal considerations. This paper proposes a novel approach using Landsat imagery and digital elevation models (DEMs) to retrieve information on storage variations in any inaccessible region. Unlike existing approaches, the method does not require any in situ measurement and is appropriate for monitoring small, and often undocumented, irrigation reservoirs. It consists of three recovery steps: (i) a 2-D dynamic classification of Landsat spectral band information to quantify the surface area of water, (ii) a statistical correction of DEM data to characterize the topography of each reservoir, and (iii) a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan Line Corrector failure. The method is applied to quantify reservoir storage in the Yarmouk basin in southern Syria, where ground monitoring is impeded by the ongoing civil war. It is validated against available in situ measurements in neighbouring Jordanian reservoirs. Coefficients of determination range from 0.69 to 0.84, and the normalized root-mean-square error from 10 to 16 % for storage estimations on six Jordanian reservoirs with maximal water surface areas ranging from 0.59 to 3.79 km2.

Identifying Key Water Resource Vulnerabilities in Data‐Scarce Transboundary River Basins

This paper presents a two‐step framework to identify key water resource vulnerabilities in transboundary river basins where data availability on both hydrological fluxes and the operation of man‐made facilities is either limited or nonexistent. In a first step, it combines two state‐of‐the‐art modeling tools to overcome data limitations and build a model that provides a lower bound on risks estimated in that basin. Land data assimilation (process‐based hydrological modeling taking remote‐sensed products as inputs) is needed to evaluate hydrological fluxes, that is, streamflow data and consumptive use in irrigated agriculture—a lower‐end estimate of demand. Hydroeconomic modeling provides cooperative water allocation policies that reflect the best‐case management of storage capacity under hydrological uncertainty at a monthly time step for competing uses—hydropower, irrigation. In a second step, the framework uses additional scenarios to proceed with the in‐depth analysis of the vulnerabilities identified despite the use of what is by definition a best‐case model. We implement this approach to the Tigris‐Euphrates river basin, a politically unstable region where water scarcity has been hypothesized to serve as a trigger for the Syrian revolution and ensuing war. Results suggest that even under the frameworks best‐case assumptions, the Euphrates part of the basin is close to a threshold where it becomes reliant on transfers of saline water from other parts of the basin to ensure irrigation demands are met. This Tigris‐Euphrates river basin application demonstrates how the proposed framework quantifies vulnerabilities that have been hitherto discussed in a mostly qualitative, speculative way.